IplImage *process(IplImage **_img)
{
fprintf(stderr, "Processing image:\n");
IplImage *img = *_img;
/* Convert to HSV */
print_time("Converting to HSV");
CvSize size = cvGetSize(img);
IplImage *hsv = cvCreateImage(size, IPL_DEPTH_8U, 3);
cvCvtColor(img, hsv, CV_BGR2HSV);
/* Generate mask */
CvMat *mask = cvCreateMat(size.height, size.width, CV_8UC1);
//cvInRangeS(hsv, cvScalar(0.11*256, 0.60*256, 0.20*256, 0),cvScalar(0.14*256, 1.00*256, 1.00*256, 0), mask);
cvInRangeS(hsv, cvScalar(0,0.6*256,0.6*256,0),cvScalar(0.21*256,256,256,0), mask);
cvReleaseImage(&hsv);
/* Perform morphological ops */
print_time("Performing morphologies");
IplConvKernel *se21 = cvCreateStructuringElementEx(21, 21, 10, 10, CV_SHAPE_RECT, NULL);
IplConvKernel *se11 = cvCreateStructuringElementEx(11, 11, 5, 5, CV_SHAPE_RECT, NULL);
cvClose(mask, mask, se21);
cvOpen(mask, mask, se11);
cvReleaseStructuringElement(&se21);
cvReleaseStructuringElement(&se11);
/* Hough transform */
IplImage *hough_in = cvCreateImage(size, 8, 1);
cvCopy(mask, hough_in, NULL);
int rows=size.height;
int cols=size.width;
int j,k;
int breakflag=0;
for(j=0;j<rows;j++) {
for(k=0;k<cols;k++)
{
CvScalar val=cvGet2D(hough_in,j,k);
if(val.val[0]==255)
{
sprintf(dat,"%d-%d:",k,j);
int rc = serialport_write(fd, dat);
if(rc==-1) return 0;
fprintf(fp,"%d %d\n",k,j);
breakflag=1;
break;
}
}
if(breakflag)
break;
}
return hough_in;
}
//形态学等级滤波器（二值,默认SE为矩形3*3）
void lhMorpRankFilterB(const IplImage* src, IplImage* dst, IplConvKernel* se = NULL, unsigned int rank = 0)
{
assert(src != NULL && dst != NULL && src != dst );
bool defaultse = false;
int card;
if (se == NULL)
{
card = 3*3;
assert(rank >= 0 && rank <= card);
se = cvCreateStructuringElementEx(3, 3, 1, 1, CV_SHAPE_RECT);
defaultse = true;
}
else
{
card = lhStructuringElementCard(se);
assert(rank >= 0 && rank <= card);
}
//default rank is median
if (rank == 0)
rank = card/2+1;
IplConvKernel* semap = lhStructuringElementMap(se);
CvMat *semat = cvCreateMat(semap->nRows, semap->nCols, CV_32FC1);
int i;
for (i=0; i<semap->nRows*semap->nCols; i++)
{
semat->data.fl[i] = semap->values[i];
}
cvThreshold(src, dst, 0, 1, CV_THRESH_BINARY);
IplImage *temp = cvCreateImage(cvGetSize(dst), 8, 1);
cvFilter2D(dst, temp, semat, cvPoint(semap->anchorX, semap->anchorY));
cvThreshold(temp, dst, card-rank, 255, CV_THRESH_BINARY);
cvReleaseMat(&semat);
cvReleaseStructuringElement(&semap);
if (defaultse)
cvReleaseStructuringElement(&se);
cvReleaseImage(&temp);
}
static gboolean gst_motiondetect_apply (
IplImage * cvReferenceImage, const IplImage * cvCurrentImage,
const IplImage * cvMaskImage, float noiseThreshold)
{
IplConvKernel *kernel = cvCreateStructuringElementEx (3, 3, 1, 1,
CV_SHAPE_ELLIPSE, NULL);
int threshold = (int)((1 - noiseThreshold) * 255);
IplImage *cvAbsDiffImage = cvReferenceImage;
double maxVal = -1.0;
cvAbsDiff( cvReferenceImage, cvCurrentImage, cvAbsDiffImage );
cvThreshold (cvAbsDiffImage, cvAbsDiffImage, threshold, 255,
CV_THRESH_BINARY);
cvErode (cvAbsDiffImage, cvAbsDiffImage, kernel, 1);
cvReleaseStructuringElement(&kernel);
cvMinMaxLoc(cvAbsDiffImage, NULL, &maxVal, NULL, NULL, cvMaskImage );
if (maxVal > 0) {
return TRUE;
} else {
return FALSE;
}
}
void BlobTracking::process(const cv::Mat &img_input, const cv::Mat &img_mask, cv::Mat &img_output)
{
if(img_input.empty() || img_mask.empty())
return;
loadConfig();
if(firstTime)
saveConfig();
IplImage* frame = new IplImage(img_input);
cvConvertScale(frame, frame, 1, 0);
IplImage* segmentated = new IplImage(img_mask);
IplConvKernel* morphKernel = cvCreateStructuringElementEx(5, 5, 1, 1, CV_SHAPE_RECT, NULL);
cvMorphologyEx(segmentated, segmentated, NULL, morphKernel, CV_MOP_OPEN, 1);
if(showBlobMask)
cvShowImage("Blob Mask", segmentated);
IplImage* labelImg = cvCreateImage(cvGetSize(frame), IPL_DEPTH_LABEL, 1);
cvb::CvBlobs blobs;
unsigned int result = cvb::cvLabel(segmentated, labelImg, blobs);
//cvb::cvFilterByArea(blobs, 500, 1000000);
cvb::cvFilterByArea(blobs, minArea, maxArea);
//cvb::cvRenderBlobs(labelImg, blobs, frame, frame, CV_BLOB_RENDER_BOUNDING_BOX);
if(debugBlob)
cvb::cvRenderBlobs(labelImg, blobs, frame, frame, CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_ANGLE|CV_BLOB_RENDER_TO_STD);
else
cvb::cvRenderBlobs(labelImg, blobs, frame, frame, CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_ANGLE);
cvb::cvUpdateTracks(blobs, tracks, 200., 5);
if(debugTrack)
cvb::cvRenderTracks(tracks, frame, frame, CV_TRACK_RENDER_ID|CV_TRACK_RENDER_BOUNDING_BOX|CV_TRACK_RENDER_TO_STD);
else
cvb::cvRenderTracks(tracks, frame, frame, CV_TRACK_RENDER_ID|CV_TRACK_RENDER_BOUNDING_BOX);
//std::map<CvID, CvTrack *> CvTracks
if(showOutput)
cvShowImage("Blob Tracking", frame);
cv::Mat img_result(frame);
img_result.copyTo(img_output);
//cvReleaseImage(&frame);
//cvReleaseImage(&segmentated);
cvReleaseImage(&labelImg);
delete frame;
delete segmentated;
cvReleaseBlobs(blobs);
cvReleaseStructuringElement(&morphKernel);
firstTime = false;
}
void catcierge_template_matcher_destroy(catcierge_matcher_t **octx)
{
catcierge_template_matcher_t *ctx;
size_t i;
if (!octx || !(*octx))
return;
ctx = (catcierge_template_matcher_t *)*octx;
if (ctx->snouts)
{
for (i = 0; i < ctx->snout_count; i++)
{
cvReleaseImage(&ctx->snouts[i]);
ctx->snouts[i] = NULL;
}
free(ctx->snouts);
ctx->snouts = NULL;
}
if (ctx->flipped_snouts)
{
for (i = 0; i < ctx->snout_count; i++)
{
cvReleaseImage(&ctx->flipped_snouts[i]);
ctx->flipped_snouts[i] = NULL;
}
free(ctx->flipped_snouts);
ctx->flipped_snouts = NULL;
}
if (ctx->storage)
{
cvReleaseMemStorage(&ctx->storage);
ctx->storage = NULL;
}
if (ctx->kernel)
{
cvReleaseStructuringElement(&ctx->kernel);
ctx->kernel = NULL;
}
if (ctx->matchres)
{
for (i = 0; i < ctx->snout_count; i++)
{
cvReleaseImage(&ctx->matchres[i]);
}
free(ctx->matchres);
ctx->matchres = NULL;
}
free(*octx);
*octx = NULL;
}
//
// function "noiseRemoval":
// applying the open morphology on the image of color segmentation
//
IplImage* noiseRemoval(IplImage* inputImage)
{
int iWidth = inputImage->width;
int iHeight = inputImage->height;
IplImage* imageNoiseRem = cvCreateImage(cvSize(iWidth,iHeight),IPL_DEPTH_8U,1);
if(!imageNoiseRem)
exit(EXIT_FAILURE);
IplConvKernel* structureEle1 =cvCreateStructuringElementEx(
3,
3,
1,
1,
CV_SHAPE_ELLIPSE,
0);
int operationType[2] = {
CV_MOP_OPEN,
CV_MOP_CLOSE
};
//seems function open and close, as well as erode and dilate reversed.
cvMorphologyEx(inputImage,imageNoiseRem,NULL,structureEle1,operationType[0],1);
//cvMorphologyEx(inputImage,imageNoiseRem,NULL,structureEle1,operationType[1],1);
//in order to connect regions breaked by mophology operation ahead
//cvErode(imageNoiseRem,imageNoiseRem,structureEle1,1);
cvReleaseStructuringElement(&structureEle1);
return imageNoiseRem;
}
//形态学约束击中-击不中变换 针对二值和灰度图像
void lhMorpHMTC(const IplImage* src, IplImage* dst, IplConvKernel* sefg, IplConvKernel* sebg =NULL)
{
assert(src != NULL && dst != NULL && src != dst && sefg!= NULL && sefg!=sebg);
if (sebg == NULL)
{
sebg = lhStructuringElementNot(sefg);
}
IplImage* temp1 = cvCreateImage(cvGetSize(src), 8, 1);
IplImage* temp2 = cvCreateImage(cvGetSize(src), 8, 1);
IplImage* temp3 = cvCreateImage(cvGetSize(src), 8, 1);
IplImage* temp4 = cvCreateImage(cvGetSize(src), 8, 1);
IplImage* mask1 = cvCreateImage(cvGetSize(src), 8, 1);
IplImage* mask2 = cvCreateImage(cvGetSize(src), 8, 1);
IplImage* mask3 = cvCreateImage(cvGetSize(src), 8, 1);
IplImage* mask4 = cvCreateImage(cvGetSize(src), 8, 1);
cvZero(mask1);
cvZero(mask2);
cvZero(mask3);
cvZero(mask4);
cvZero(dst);
//P107 (5.5)
cvErode( src, temp1, sebg);
cvDilate( src, temp2, sebg);
cvErode( src, temp3, sefg);
cvDilate( src, temp4, sefg);
cvCmp(src, temp3, mask1, CV_CMP_EQ);
cvCmp(temp2, src, mask2, CV_CMP_LT);
cvAnd(mask1, mask2, mask2);
cvCmp(src, temp4, mask3 , CV_CMP_EQ);
cvCmp(temp1, src, mask4 , CV_CMP_GT);
cvAnd(mask3, mask4, mask4);
cvSub(src, temp2, dst, mask2);
cvSub(temp1, src, dst, mask4);
cvReleaseImage(&mask1);
cvReleaseImage(&mask2);
cvReleaseImage(&mask3);
cvReleaseImage(&mask4);
cvReleaseImage(&temp1);
cvReleaseImage(&temp2);
cvReleaseImage(&temp3);
cvReleaseImage(&temp4);
cvReleaseStructuringElement(&sebg);
}
//形态学非约束击中-击不中变换 针对二值和灰度图像
void lhMorpHMTU(const IplImage* src, IplImage* dst, IplConvKernel* sefg, IplConvKernel* sebg =NULL)
{
assert(src != NULL && dst != NULL && src != dst && sefg!= NULL && sefg!=sebg);
if (sebg == NULL)
{
sebg = lhStructuringElementNot(sefg);
}
IplImage* temp = cvCreateImage(cvGetSize(src), 8, 1);
IplImage* mask = cvCreateImage(cvGetSize(src), 8, 1);
cvZero(mask);
//P106 (5.4)
cvErode( src, temp, sefg);
cvDilate(src, dst, sebg);
cvCmp(temp, dst, mask, CV_CMP_GT);
cvSub(temp, dst, dst, mask);
cvNot(mask, mask);
cvSet(dst, cvScalar(0), mask);
//cvCopy(dst, mask);
//cvSet(dst, cvScalar(255), mask);
cvReleaseImage(&mask);
cvReleaseImage(&temp);
cvReleaseStructuringElement(&sebg);
}
//形态学二值击中-击不中变换
void lhMorpHMTB(const IplImage* src, IplImage* dst, IplConvKernel* sefg, IplConvKernel* sebg =NULL)
{
assert(src != NULL && dst != NULL && src != dst && sefg!= NULL && sefg!=sebg);
if (sebg == NULL)
{
sebg = lhStructuringElementNot(sefg);
}
IplImage* temp1 = cvCreateImage(cvGetSize(src), 8, 1);
IplImage* temp2 = cvCreateImage(cvGetSize(src), 8, 1);
//P104 (5.2)
cvErode( src, temp1, sefg);
cvNot(src, temp2);
cvErode( temp2, temp2, sebg);
cvAnd(temp1, temp2, dst);
cvReleaseImage(&temp1);
cvReleaseImage(&temp2);
cvReleaseStructuringElement(&sebg);
}
//形态学方向梯度
void lhMorpGradientDir(const IplImage* src, IplImage* dst, unsigned int angle, unsigned int len )
{
assert(src != NULL && dst != NULL && src != dst);
IplConvKernel* se = lhStructuringElementLine(angle, len);
lhMorpGradient(src, dst, se);
cvReleaseStructuringElement(&se);
}
static av_cold void dilate_uninit(AVFilterContext *ctx)
{
OCVContext *ocv = ctx->priv;
DilateContext *dilate = ocv->priv;
cvReleaseStructuringElement(&dilate->kernel);
}
IplImage *contoursGetOutlineMorh(IplImage *src, IplImage *temp, int mask)
{
int radius = 3;
int cols = radius * 2 + 1;
int rows = cols;
IplImage *res;
IplImage *bin = cvCreateImage(cvGetSize(src), src->depth, 1);
cvAdaptiveThreshold(src, bin, 255, CV_ADAPTIVE_THRESH_GAUSSIAN_C, CV_THRESH_BINARY, 7, 1);
if (mask == 1) {
IplImage *mask = cvCreateImage(cvGetSize(src), src->depth, 1);
res = cvCreateImage(cvGetSize(src), src->depth, 1);
cvThreshold(src, mask, 0, 255, CV_THRESH_BINARY_INV + CV_THRESH_OTSU);
cvOr(bin, mask, res, NULL);
cvReleaseImage(&mask);
} else {
res = bin;
}
IplConvKernel *element = cvCreateStructuringElementEx(cols, rows, radius, radius, CV_SHAPE_ELLIPSE, NULL);
cvMorphologyEx(res, res, temp, element, CV_MOP_OPEN, 1);
cvReleaseStructuringElement(&element);
radius = 9;
cols = radius * 2 + 1;
rows = cols;
element = cvCreateStructuringElementEx(cols, rows, radius, radius, CV_SHAPE_ELLIPSE, NULL);
cvMorphologyEx(res, res, temp, element, CV_MOP_CLOSE, 1);
cvReleaseStructuringElement(&element);
radius = 7;
cols = radius * 2 + 1;
rows = cols;
element = cvCreateStructuringElementEx(cols, rows, radius, radius, CV_SHAPE_ELLIPSE, NULL);
cvErode(res, res, element, 1);
cvDilate(res, res, element, 1);
contoursDrawBorder(res);
cvReleaseStructuringElement(&element);
cvReleaseImage(&temp);
return res;
}
IplImage *closeImage(IplImage *source) {
int radius = 3;
IplConvKernel* Kern = cvCreateStructuringElementEx(radius*2+1, radius*2+1, radius, radius, CV_SHAPE_RECT, NULL);
cvErode(source, source, Kern, 1);
cvDilate(source, source, Kern, 1);
cvReleaseStructuringElement(&Kern);
return source;
}
/*
* Transform the image into a two colored image, one color for the color we want to track, another color for the others colors
* From this image, we get two datas : the number of pixel detected, and the center of gravity of these pixel
*/
CvPoint binarisation(IplImage* image, int *nbPixels) {
int x, y;
CvScalar pixel;
IplImage *hsv, *mask;
IplConvKernel *kernel;
int sommeX = 0, sommeY = 0;
*nbPixels = 0;
// Create the mask &initialize it to white (no color detected)
mask = cvCreateImage(cvGetSize(image), image->depth, 1);
// Create the hsv image
hsv = cvCloneImage(image);
cvCvtColor(image, hsv, CV_BGR2HSV);
cvShowImage("GeckoGeek Color Rectification", hsv);
// We create the mask
cvInRangeS(hsv, cvScalar(h - tolerance -1, s - tolerance, 0), cvScalar(h + tolerance -1, s + tolerance, 255), mask);
// Create kernels for the morphological operation
kernel = cvCreateStructuringElementEx(5, 5, 2, 2, CV_SHAPE_ELLIPSE);
// Morphological opening (inverse because we have white pixels on black background)
cvDilate(mask, mask, kernel, 1);
cvErode(mask, mask, kernel, 1);
// We go through the mask to look for the tracked object and get its gravity center
for(x = 0; x < mask->width; x++) {
for(y = 0; y < mask->height; y++) {
// If its a tracked pixel, count it to the center of gravity's calcul
if(((uchar *)(mask->imageData + y*mask->widthStep))[x] == 255) {
sommeX += x;
sommeY += y;
(*nbPixels)++;
}
}
}
// Show the result of the mask image
cvShowImage("GeckoGeek Mask", mask);
// We release the memory of kernels
cvReleaseStructuringElement(&kernel);
// We release the memory of the mask
cvReleaseImage(&mask);
// We release the memory of the hsv image
cvReleaseImage(&hsv);
// If there is no pixel, we return a center outside the image, else we return the center of gravity
if(*nbPixels > 0)
return cvPoint((int)(sommeX / (*nbPixels)), (int)(sommeY / (*nbPixels)));
else
return cvPoint(-1, -1);
}
void catcierge_haar_matcher_destroy(catcierge_matcher_t **octx)
{
catcierge_haar_matcher_t *ctx;
if (!octx || !(*octx))
return;
ctx = (catcierge_haar_matcher_t *)*octx;
if (ctx->cascade)
{
cv2CascadeClassifier_destroy(ctx->cascade);
ctx->cascade = NULL;
}
if (ctx->kernel2x2)
{
cvReleaseStructuringElement(&ctx->kernel2x2);
ctx->kernel2x2 = NULL;
}
if (ctx->kernel3x3)
{
cvReleaseStructuringElement(&ctx->kernel3x3);
ctx->kernel3x3 = NULL;
}
if (ctx->kernel5x1)
{
cvReleaseStructuringElement(&ctx->kernel5x1);
ctx->kernel5x1 = NULL;
}
if (ctx->storage)
{
cvReleaseMemStorage(&ctx->storage);
ctx->storage = NULL;
}
free(ctx);
*octx = NULL;
}
//形态学闭运算
void lhMorpClose(const IplImage* src, IplImage* dst, IplConvKernel* se=NULL, int iterations=1)
{
cvDilate( src, dst, se, iterations );
IplConvKernel* semap = lhStructuringElementMap(se);
cvErode( dst, dst, semap, iterations );
cvReleaseStructuringElement(&semap);
}
CV_IMPL IplConvKernel *
cvCreateStructuringElementEx( int cols, int rows,
int anchorX, int anchorY,
int shape, int *values )
{
IplConvKernel *element = 0;
int i, size = rows * cols;
int element_size = sizeof(*element) + size*sizeof(element->values[0]);
CV_FUNCNAME( "cvCreateStructuringElementEx" );
__BEGIN__;
if( !values && shape == CV_SHAPE_CUSTOM )
CV_ERROR_FROM_STATUS( CV_NULLPTR_ERR );
if( cols <= 0 || rows <= 0 ||
(unsigned) anchorX >= (unsigned) cols ||
(unsigned) anchorY >= (unsigned) rows )
CV_ERROR_FROM_STATUS( CV_BADSIZE_ERR );
CV_CALL( element = (IplConvKernel *)cvAlloc(element_size + 32));
if( !element )
CV_ERROR_FROM_STATUS( CV_OUTOFMEM_ERR );
element->nCols = cols;
element->nRows = rows;
element->anchorX = anchorX;
element->anchorY = anchorY;
element->nShiftR = shape < CV_SHAPE_ELLIPSE ? shape : CV_SHAPE_CUSTOM;
element->values = (int*)(element + 1);
if( shape == CV_SHAPE_CUSTOM )
{
if( !values )
CV_ERROR( CV_StsNullPtr, "Null pointer to the custom element mask" );
for( i = 0; i < size; i++ )
element->values[i] = values[i];
}
else
{
CvMat el_hdr = cvMat( rows, cols, CV_32SC1, element->values );
CV_CALL( CvMorphology::init_binary_element(&el_hdr,
shape, cvPoint(anchorX,anchorY)));
}
__END__;
if( cvGetErrStatus() < 0 )
cvReleaseStructuringElement( &element );
return element;
}
/*
* Release IplConvKernel object from memory and delete from hashtable.
*/
void
release_iplconvkernel_object(void *ptr)
{
if (ptr) {
unregister_object(ptr);
try {
cvReleaseStructuringElement((IplConvKernel**)(&ptr));
}
catch (cv::Exception& e) {
raise_cverror(e);
}
}
}
/*
* Transform the image into a two colored image, one color for the color we want to track, another color for the others colors
* From this image, we get two datas : the number of pixel detected, and the center of gravity of these pixel
*/
CvPoint ColourToTrack::binarise(IplImage* image)
{
int x, y;
IplImage *hsv;
IplConvKernel *kernel;
int sommeX = 0, sommeY = 0;
nbPixels = 0;
if(mask==NULL) mask = cvCreateImage(cvGetSize(image), image->depth, 1);
// Create the hsv image
hsv = cvCloneImage(image);
//cvCvtColor(image, hsv, CV_BGR2HSV);
cvCvtColor(image, hsv, CV_BGR2Lab);
// We create the mask
//cvInRangeS(hsv, cvScalar(colour.hsv.h - TOLERANCE -1, colour.hsv.s - TOLERANCE, 0), cvScalar(colour.hsv.h + TOLERANCE -1, colour.hsv.s + TOLERANCE, 255), mask);
cvInRangeS(hsv, cvScalar(0, colour.hsv.s - TOLERANCE -1, colour.hsv.v - TOLERANCE), cvScalar(255, colour.hsv.s + TOLERANCE -1, colour.hsv.v + TOLERANCE), mask);
// Create kernels for the morphological operation
kernel = cvCreateStructuringElementEx(5, 5, 2, 2, CV_SHAPE_ELLIPSE);
// Morphological closing (inverse because we have white pixels on black background)
cvDilate(mask, mask, kernel, 1);
cvErode(mask, mask, kernel, 1);
// We go through the mask to look for the tracked object and get its gravity center
for(x = 0; x < mask->width; x++) {
for(y = 0; y < mask->height; y++) {
// If it's a tracked pixel, count it to the center of gravity's calcul
if(((uchar *)(mask->imageData + y*mask->widthStep))[x] == 255) {
sommeX += x;
sommeY += y;
nbPixels++;
}
}
}
// We release the memory of kernels
cvReleaseStructuringElement(&kernel);
// We release the memory of the hsv image
cvReleaseImage(&hsv);
// If there is no pixel, we return a center outside the image, else we return the center of gravity
if(nbPixels > 0)
return cvPoint((int)(sommeX / (nbPixels)), (int)(sommeY / (nbPixels)));
else
return cvPoint(-1, -1);
}
void CTransformImage::Morphology()
{
if(!m_transImage)
return;
IplConvKernel* element = cvCreateStructuringElementEx(3, 3, 1, 1, CV_SHAPE_RECT, NULL);
cvDilate(m_transImage, m_transImage, element, 1);
cvDilate(m_transImage, m_transImage, element, 1);
cvErode (m_transImage, m_transImage, element, 1);
cvErode (m_transImage, m_transImage, element, 1);
cvReleaseStructuringElement(&element);
}
//形态学击中-击不中开变换
void lhMorpHMTOpen(const IplImage* src, IplImage* dst, IplConvKernel* sefg, IplConvKernel* sebg =NULL, int type=LH_MORP_TYPE_BINARY)
{
assert(src != NULL && dst != NULL && src != dst && sefg!= NULL && sefg!=sebg);
IplConvKernel* semap = lhStructuringElementMap(sefg);
IplImage* temp = cvCreateImage(cvGetSize(src), 8, 1);
//P110 (5.8)
lhMorpHMT(src, temp, sefg, sebg, type);
cvDilate(temp, dst, semap);
cvReleaseImage(&temp);
cvReleaseStructuringElement(&semap);
}
// callback function for erode/dilate trackbar
void ErodeDilate(int pos)
{
int n = erode_dilate_pos - max_iters;
int an = n > 0 ? n : -n;
element = cvCreateStructuringElementEx( an*2+1, an*2+1, an, an, element_shape, 0 );
if( n < 0 )
{
cvErode(src,dst,element,1);
}
else
{
cvDilate(src,dst,element,1);
}
cvReleaseStructuringElement(&element);
cvShowImage("Erode/Dilate",dst);
}
// callback function for open/close trackbar
void OpenClose(int pos)
{
int n = open_close_pos - max_iters;
int an = n > 0 ? n : -n;
element = cvCreateStructuringElementEx( an*2+1, an*2+1, an, an, element_shape, 0 );
if( n < 0 )
{
cvErode(src,dst,element,1);
cvDilate(dst,dst,element,1);
}
else
{
cvDilate(src,dst,element,1);
cvErode(dst,dst,element,1);
}
cvReleaseStructuringElement(&element);
cvShowImage("Open/Close",dst);
}
DMZ_INTERNAL void prepare_image_for_cat(IplImage *image, IplImage *as_float, CharacterRectListIterator rect) {
// Input image: IPL_DEPTH_8U [0 - 255]
// Data for models: IPL_DEPTH_32F [0.0 - 1.0]
cvSetImageROI(image, cvRect(rect->left, rect->top, kTrimmedCharacterImageWidth, kTrimmedCharacterImageHeight));
// TODO: optimize this a lot!
// Gradient
IplImage *filtered_image = cvCreateImage(cvSize(kTrimmedCharacterImageWidth, kTrimmedCharacterImageHeight), IPL_DEPTH_8U, 1);
//llcv_morph_grad3_2d_cross_u8(image, filtered_image);
IplConvKernel *kernel = cvCreateStructuringElementEx(3, 3, 1, 1, CV_SHAPE_CROSS, NULL);
cvMorphologyEx(image, filtered_image, NULL, kernel, CV_MOP_GRADIENT, 1);
cvReleaseStructuringElement(&kernel);
// Equalize
llcv_equalize_hist(filtered_image, filtered_image);
// Bilateral filter
int aperture = 3;
double space_sigma = (aperture / 2.0 - 1) * 0.3 + 0.8;
double color_sigma = (aperture - 1) / 3.0;
IplImage *smoothed_image = cvCreateImage(cvSize(kTrimmedCharacterImageWidth, kTrimmedCharacterImageHeight), IPL_DEPTH_8U, 1);
cvSmooth(filtered_image, smoothed_image, CV_BILATERAL, aperture, aperture, space_sigma, color_sigma);
// Convert to float
cvConvertScale(smoothed_image, as_float, 1.0f / 255.0f, 0);
cvReleaseImage(&smoothed_image);
cvReleaseImage(&filtered_image);
cvResetImageROI(image);
#if DEBUG_EXPIRY_CATEGORIZATION_PERFORMANCE
dmz_debug_timer_print("prepare image", 2);
#endif
}
int main( int argc, char** argv )
{
IplImage* img;
IplImage* mask2; //ÉùÃ÷IplImageÖ¸Õë
CvRect r;
//ÔØÈëͼÏñ
img = cvLoadImage( "tennis_input.jpg",1);
cvNamedWindow( "originalImage", 1 );//´´½¨´°¿Ú
cvShowImage( "originalImage", img );//ÏÔʾͼÏñ
CvSize size = cvGetSize(img);
IplImage *hsv = cvCreateImage(size, IPL_DEPTH_8U, 3);
cvCvtColor(img, hsv, CV_BGR2HSV);
CvMat *mask = cvCreateMat(size.height, size.width, CV_8UC1);
mask2 = cvCreateImage(size, IPL_DEPTH_8U,3);
cvInRangeS(hsv, cvScalar(0.11*256, 0.60*256, 0.20*256, 0), cvScalar(0.14*256, 1.00*256, 1.00*256, 0), mask);
cvReleaseImage(&hsv);
IplConvKernel *se21 = cvCreateStructuringElementEx(21, 21, 10, 10, CV_SHAPE_RECT, NULL);
IplConvKernel *se11 = cvCreateStructuringElementEx(11, 11, 5, 5, CV_SHAPE_RECT, NULL);
cvNamedWindow( "Mask before", 1 );//´´½¨´°¿Ú
cvShowImage( "Mask before", mask );//ÏÔʾͼÏñ
//cvClose(mask, mask, se21); See completed example for cvClose definition
cvDilate(mask, mask, se21,1);
cvErode(mask, mask, se21,1);
//cvOpen(mask, mask, se11); See completed example for cvOpen definition
cvErode(mask, mask, se11,1);
cvDilate(mask, mask, se11,1);
cvReleaseStructuringElement(&se21);
cvReleaseStructuringElement(&se11);
/* Copy mask into a grayscale image */
IplImage *hough_in = cvCreateImage(size, 8, 1);
cvCopy(mask, hough_in, NULL);
cvCvtColor( mask, mask2, CV_GRAY2BGR );
cvSmooth(hough_in, hough_in, CV_GAUSSIAN, 15, 15, 0, 0);
/* Run the Hough function */
CvMemStorage *storage = cvCreateMemStorage(0);
//CvSeq *circles = cvHoughCircles(hough_in, storage, CV_HOUGH_GRADIENT, 4, size.height/10, 50, 150, 0, 0);
CvSeq *contour;
cvFindContours( hough_in, storage, &contour, sizeof(CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );
for(;contour;contour=contour->h_next)
{
r=((CvContour*)contour)->rect;
//ÔÚͼÖл³ö¾ØÐοò
cvRectangle(img,cvPoint(r.x,r.y),cvPoint(r.x+r.width,r.y+r.height),CV_RGB(255,0,0),3,CV_AA,0);
cvRectangle(mask2,cvPoint(r.x,r.y),cvPoint(r.x+r.width,r.y+r.height),CV_RGB(255,0,0),3,CV_AA,0);
}
cvReleaseMemStorage(&storage);
cvNamedWindow( "Image", 1 );//´´½¨´°¿Ú
cvShowImage( "Image", img );//ÏÔʾͼÏñ
cvNamedWindow( "Mask", 1 );//´´½¨´°¿Ú
cvShowImage( "Mask", mask );//ÏÔʾͼÏñ
cvNamedWindow( "Mask2", 1 );//´´½¨´°¿Ú
cvShowImage( "Mask2", mask2 );//ÏÔʾͼÏñ
cvWaitKey(0); //µÈ´ý°´¼ü
cvDestroyWindow( "Image" );//Ïú»Ù´°¿Ú
cvReleaseImage( &img ); //ÊÍ·ÅͼÏñ
cvDestroyWindow( "Mask" );//Ïú»Ù´°¿Ú
cvDestroyWindow( "Mask before" );//Ïú»Ù´°¿Ú
cvDestroyWindow( "Original" );//Ïú»Ù´°¿Ú
cvDestroyWindow( "Mask2" );//Ïú»Ù´°¿Ú
return 0;
}
//---------------------------------------------------------
bool COpenCV_Morphology::On_Execute(void)
{
int Type, Shape, Radius, Iterations;
CSG_Grid *pInput, *pOutput;
pInput = Parameters("INPUT") ->asGrid();
pOutput = Parameters("OUTPUT") ->asGrid();
Type = Parameters("TYPE") ->asInt();
Shape = Parameters("SHAPE") ->asInt();
Radius = Parameters("RADIUS") ->asInt();
Iterations = Parameters("ITERATIONS") ->asInt();
//-----------------------------------------------------
switch( Shape )
{
default:
case 0: Shape = CV_SHAPE_ELLIPSE; break;
case 1: Shape = CV_SHAPE_RECT; break;
case 2: Shape = CV_SHAPE_CROSS; break;
}
//-----------------------------------------------------
IplImage *cv_pInput = Get_CVImage(pInput);
IplImage *cv_pOutput = Get_CVImage(Get_NX(), Get_NY(), pInput->Get_Type());
IplImage *cv_pTmp = NULL;
//-----------------------------------------------------
IplConvKernel *cv_pElement = cvCreateStructuringElementEx(Radius * 2 + 1, Radius * 2 + 1, Radius, Radius, Shape, 0);
switch( Type )
{
case 0: // dilation
cvDilate (cv_pInput, cv_pOutput, cv_pElement, Iterations);
break;
case 1: // erosion
cvErode (cv_pInput, cv_pOutput, cv_pElement, Iterations);
break;
case 2: // opening
cvMorphologyEx (cv_pInput, cv_pOutput, cv_pTmp,
cv_pElement, CV_MOP_OPEN , Iterations
);
break;
case 3: // closing
cvMorphologyEx (cv_pInput, cv_pOutput, cv_pTmp,
cv_pElement, CV_MOP_CLOSE , Iterations
);
break;
case 4: // morpological gradient
cvMorphologyEx (cv_pInput, cv_pOutput, cv_pTmp = Get_CVImage(Get_NX(), Get_NY(), pInput->Get_Type()),
cv_pElement, CV_MOP_GRADIENT, Iterations
);
break;
case 5: // top hat
cvMorphologyEx (cv_pInput, cv_pOutput, cv_pTmp = Get_CVImage(Get_NX(), Get_NY(), pInput->Get_Type()),
cv_pElement, CV_MOP_TOPHAT , Iterations
);
break;
case 6: // black hat
cvMorphologyEx (cv_pInput, cv_pOutput, cv_pTmp = Get_CVImage(Get_NX(), Get_NY(), pInput->Get_Type()),
cv_pElement, CV_MOP_BLACKHAT, Iterations
);
break;
}
cvReleaseStructuringElement(&cv_pElement);
//-----------------------------------------------------
Copy_CVImage_To_Grid(pOutput, cv_pOutput);
cvReleaseImage(&cv_pInput);
cvReleaseImage(&cv_pOutput);
if( cv_pTmp )
{
cvReleaseImage(&cv_pTmp);
}
pOutput->Set_Name(CSG_String::Format(SG_T("%s [%s]"), pInput->Get_Name(), Get_Name().c_str()));
return( true );
}
int main(int argc, char* argv[])
{
if( argc != 3 )
{
fprintf(stderr, "Usage: %s panorender.png photo.jpg\n", argv[0]);
return 1;
}
IplImage* pano = cvLoadImage( argv[1], CV_LOAD_IMAGE_COLOR); assert(pano);
IplImage* img = cvLoadImage( argv[2], CV_LOAD_IMAGE_COLOR); assert(img);
CvMat* pano_edges;
CvMat* img_edges;
{
pano_edges = extractEdges(pano, PANO);
cvThreshold( pano_edges, pano_edges, 200.0, 0, CV_THRESH_TOZERO );
// the non-edge areas of the panorama should be dont-care areas. I implement
// this by
// x -> dilate ? x : mean;
// another way to state the same thing:
// !dilate -> mask
// cvSet(mean)
#define DILATE_R 9
#define EDGE_MINVAL 180
IplConvKernel* kernel = cvCreateStructuringElementEx( 2*DILATE_R + 1, 2*DILATE_R + 1,
DILATE_R, DILATE_R,
CV_SHAPE_ELLIPSE, NULL);
CvMat* dilated = cvCreateMat( pano->height, pano->width, CV_8UC1 );
cvDilate(pano_edges, dilated, kernel, 1);
CvScalar avg = cvAvg(pano_edges, dilated);
cvCmpS(dilated, EDGE_MINVAL, dilated, CV_CMP_LT);
cvSet( pano_edges, avg, dilated );
cvReleaseMat(&dilated);
cvReleaseStructuringElement(&kernel);
}
{
img_edges = extractEdges(img, PHOTO);
cvSmooth(img_edges, img_edges, CV_GAUSSIAN, 13, 13, 0.0, 0.0);
}
CvPoint offset = alignImages( img_edges, pano_edges );
printf("offset: x,y: %d %d\n", offset.x, offset.y );
cvReleaseMat ( &pano_edges );
cvReleaseMat ( &img_edges );
cvReleaseImage( &pano );
cvReleaseImage( &img );
return 0;
}
DLLEXPORT int opencv_dilate(WolframLibraryData libData, mint Argc, MArgument *Args, MArgument res)
{
mint dims[3], w, h, i, j;
IplImage* src = 0;
IplImage* dst = 0;
raw_t_bit* src_data_bit = 0;
raw_t_bit* dst_data_bit = 0;
raw_t_ubit8* src_data_byte = 0;
raw_t_ubit8* dst_data_byte = 0;
raw_t_ubit16* src_data_bit16 = 0;
raw_t_ubit16* dst_data_bit16 = 0;
raw_t_real32* src_data_real32 = 0;
raw_t_real32* dst_data_real32 = 0;
IplConvKernel* element = 0;
MImage image_in, image_out = 0;
int radius;
int err = 0;
int type = 0;
WolframImageLibrary_Functions imgFuns = libData->imageLibraryFunctions;
if (Argc < 2) {
return LIBRARY_FUNCTION_ERROR;
}
image_in = MArgument_getMImage(Args[0]);
if(imgFuns->MImage_getRank(image_in) == 3) return LIBRARY_FUNCTION_ERROR;
if(imgFuns->MImage_getChannels(image_in) != 1) return LIBRARY_FUNCTION_ERROR;
radius = MArgument_getInteger(Args[1]);
if(radius < 1) return LIBRARY_FUNCTION_ERROR;
err = imgFuns->MImage_clone(image_in, &image_out);
if (err) return LIBRARY_FUNCTION_ERROR;
type = imgFuns->MImage_getDataType(image_in);
h = imgFuns->MImage_getRowCount(image_in);
w = imgFuns->MImage_getColumnCount(image_in);
element = cvCreateStructuringElementEx(2*radius+1,2*radius+1, radius, radius, CV_SHAPE_RECT, 0);
switch(type) {
case MImage_Type_Bit:
{
raw_t_bit* data_in = imgFuns->MImage_getBitData(image_in);
raw_t_bit* data_out = imgFuns->MImage_getBitData(image_out);
if (!data_in || !data_out) {
err = LIBRARY_FUNCTION_ERROR;
goto cleanup;
}
src = cvCreateImage( cvSize(w, h), IPL_DEPTH_1U, 1);
dst = cvCreateImage( cvSize(w, h), IPL_DEPTH_1U, 1);
src_data_bit = src->imageData;
dst_data_bit = dst->imageData;
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
(src_data_bit + i*src->widthStep)[j] = data_in[i*w+j];
}
}
cvDilate(src, dst, element, 1);
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
data_out[i*w+j] = (dst_data_bit + i*dst->widthStep)[j];
}
}
break;
}
case MImage_Type_Bit8:
{
raw_t_ubit8* data_in = imgFuns->MImage_getByteData(image_in);
raw_t_ubit8* data_out = imgFuns->MImage_getByteData(image_out);
if (!data_in || !data_out) {
err = LIBRARY_FUNCTION_ERROR;
goto cleanup;
}
src = cvCreateImage( cvSize(w, h), IPL_DEPTH_8U, 1);
dst = cvCreateImage( cvSize(w, h), IPL_DEPTH_8U, 1);
src_data_byte = src->imageData;
dst_data_byte = dst->imageData;
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
(src_data_byte + i*src->widthStep)[j] = data_in[i*w+j];
}
}
cvDilate(src, dst, element, 1);
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
data_out[i*w+j] = (dst_data_byte + i*dst->widthStep)[j];
}
}
break;
}
case MImage_Type_Bit16:
{
raw_t_ubit16* data_in = imgFuns->MImage_getBit16Data(image_in);
raw_t_ubit16* data_out = imgFuns->MImage_getBit16Data(image_out);
if (!data_in || !data_out) {
err = LIBRARY_FUNCTION_ERROR;
goto cleanup;
}
src = cvCreateImage( cvSize(w, h), IPL_DEPTH_16U, 1);
dst = cvCreateImage( cvSize(w, h), IPL_DEPTH_16U, 1);
src_data_bit16 = src->imageData;
dst_data_bit16 = dst->imageData;
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
(src_data_bit16 + i*src->widthStep)[j] = data_in[i*w+j];
}
}
cvDilate(src, dst, element, 1);
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
data_out[i*w+j] = (dst_data_bit16 + i*dst->widthStep)[j];
}
}
break;
}
case MImage_Type_Real32:
{
raw_t_real32* data_in = imgFuns->MImage_getReal32Data(image_in);
raw_t_real32* data_out = imgFuns->MImage_getReal32Data(image_out);
if (!data_in || !data_out) {
err = LIBRARY_FUNCTION_ERROR;
goto cleanup;
}
src = cvCreateImage( cvSize(w, h), IPL_DEPTH_32F, 1);
dst = cvCreateImage( cvSize(w, h), IPL_DEPTH_32F, 1);
src_data_real32 = src->imageData;
dst_data_real32 = dst->imageData;
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
(src_data_real32 + i*src->widthStep)[j] = data_in[i*w+j];
}
}
cvDilate(src, dst, element, 1);
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
data_out[i*w+j] = (dst_data_real32 + i*dst->widthStep)[j];
}
}
break;
}
case MImage_Type_Real:
{
raw_t_real64* data_in = imgFuns->MImage_getRealData(image_in);
raw_t_real64* data_out = imgFuns->MImage_getRealData(image_out);
if (!data_in || !data_out) {
err = LIBRARY_FUNCTION_ERROR;
goto cleanup;
}
src = cvCreateImage( cvSize(w, h), IPL_DEPTH_32F, 1);
dst = cvCreateImage( cvSize(w, h), IPL_DEPTH_32F, 1);
src_data_real32 = src->imageData;
dst_data_real32 = dst->imageData;
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
(src_data_real32 + i*src->widthStep)[j] = (raw_t_real32)data_in[i*w+j];
}
}
cvDilate(src, dst, element, 1);
for (i = 0; i < h; i++) {
for (j = 0; j < w; j++) {
data_out[i*w+j] = (dst_data_real32 + i*dst->widthStep)[j];
}
}
break;
}
default:
return LIBRARY_FUNCTION_ERROR;
}
cleanup:
if(src) cvReleaseImage( &src );
if(dst) cvReleaseImage( &dst );
if(element) cvReleaseStructuringElement(&element);
if(err == 0) {
MArgument_setMImage(res, image_out);
}
else {
if(image_out) imgFuns->MImage_free(image_out);
}
return err;
}
IplImage * find_macbeth( const char *img )
{
IplImage * macbeth_img = cvLoadImage( img,
CV_LOAD_IMAGE_ANYCOLOR|CV_LOAD_IMAGE_ANYDEPTH );
IplImage * macbeth_original = cvCreateImage( cvSize(macbeth_img->width, macbeth_img->height), macbeth_img->depth, macbeth_img->nChannels );
cvCopy(macbeth_img, macbeth_original);
IplImage * macbeth_split[3];
IplImage * macbeth_split_thresh[3];
for(int i = 0; i < 3; i++) {
macbeth_split[i] = cvCreateImage( cvSize(macbeth_img->width, macbeth_img->height), macbeth_img->depth, 1 );
macbeth_split_thresh[i] = cvCreateImage( cvSize(macbeth_img->width, macbeth_img->height), macbeth_img->depth, 1 );
}
cvSplit(macbeth_img, macbeth_split[0], macbeth_split[1], macbeth_split[2], NULL);
if( macbeth_img )
{
int adaptive_method = CV_ADAPTIVE_THRESH_MEAN_C;
int threshold_type = CV_THRESH_BINARY_INV;
int block_size = cvRound(
MIN(macbeth_img->width,macbeth_img->height)*0.02)|1;
fprintf(stderr,"Using %d as block size\n", block_size);
double offset = 6;
// do an adaptive threshold on each channel
for(int i = 0; i < 3; i++) {
cvAdaptiveThreshold(macbeth_split[i], macbeth_split_thresh[i], 255, adaptive_method, threshold_type, block_size, offset);
}
IplImage * adaptive = cvCreateImage( cvSize(macbeth_img->width, macbeth_img->height), IPL_DEPTH_8U, 1 );
// OR the binary threshold results together
cvOr(macbeth_split_thresh[0],macbeth_split_thresh[1],adaptive);
cvOr(macbeth_split_thresh[2],adaptive,adaptive);
for(int i = 0; i < 3; i++) {
cvReleaseImage( &(macbeth_split[i]) );
cvReleaseImage( &(macbeth_split_thresh[i]) );
}
int element_size = (block_size/10)+2;
fprintf(stderr,"Using %d as element size\n", element_size);
// do an opening on the threshold image
IplConvKernel * element = cvCreateStructuringElementEx(element_size,element_size,element_size/2,element_size/2,CV_SHAPE_RECT);
cvMorphologyEx(adaptive,adaptive,NULL,element,CV_MOP_OPEN);
cvReleaseStructuringElement(&element);
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* initial_quads = cvCreateSeq( 0, sizeof(*initial_quads), sizeof(void*), storage );
CvSeq* initial_boxes = cvCreateSeq( 0, sizeof(*initial_boxes), sizeof(CvBox2D), storage );
// find contours in the threshold image
CvSeq * contours = NULL;
cvFindContours(adaptive,storage,&contours);
int min_size = (macbeth_img->width*macbeth_img->height)/
(MACBETH_SQUARES*100);
if(contours) {
int count = 0;
for( CvSeq* c = contours; c != NULL; c = c->h_next) {
CvRect rect = ((CvContour*)c)->rect;
// only interested in contours with these restrictions
if(CV_IS_SEQ_HOLE(c) && rect.width*rect.height >= min_size) {
// only interested in quad-like contours
CvSeq * quad_contour = find_quad(c, storage, min_size);
if(quad_contour) {
cvSeqPush( initial_quads, &quad_contour );
count++;
rect = ((CvContour*)quad_contour)->rect;
CvScalar average = contour_average((CvContour*)quad_contour, macbeth_img);
CvBox2D box = cvMinAreaRect2(quad_contour,storage);
cvSeqPush( initial_boxes, &box );
// fprintf(stderr,"Center: %f %f\n", box.center.x, box.center.y);
double min_distance = MAX_RGB_DISTANCE;
CvPoint closest_color_idx = cvPoint(-1,-1);
for(int y = 0; y < MACBETH_HEIGHT; y++) {
for(int x = 0; x < MACBETH_WIDTH; x++) {
double distance = euclidean_distance_lab(average,colorchecker_srgb[y][x]);
if(distance < min_distance) {
closest_color_idx.x = x;
closest_color_idx.y = y;
min_distance = distance;
}
}
}
CvScalar closest_color = colorchecker_srgb[closest_color_idx.y][closest_color_idx.x];
// fprintf(stderr,"Closest color: %f %f %f (%d %d)\n",
// closest_color.val[2],
// closest_color.val[1],
// closest_color.val[0],
// closest_color_idx.x,
// closest_color_idx.y
// );
// cvDrawContours(
// macbeth_img,
// quad_contour,
// cvScalar(255,0,0),
// cvScalar(0,0,255),
// 0,
// element_size
// );
// cvCircle(
// macbeth_img,
// cvPointFrom32f(box.center),
// element_size*6,
// cvScalarAll(255),
// -1
// );
// cvCircle(
// macbeth_img,
// cvPointFrom32f(box.center),
// element_size*6,
// closest_color,
// -1
// );
// cvCircle(
// macbeth_img,
// cvPointFrom32f(box.center),
// element_size*4,
// average,
// -1
// );
// CvRect rect = contained_rectangle(box);
// cvRectangle(
// macbeth_img,
// cvPoint(rect.x,rect.y),
// cvPoint(rect.x+rect.width, rect.y+rect.height),
// cvScalarAll(0),
// element_size
// );
}
}
}
ColorChecker found_colorchecker;
fprintf(stderr,"%d initial quads found", initial_quads->total);
if(count > MACBETH_SQUARES) {
fprintf(stderr," (probably a Passport)\n");
CvMat* points = cvCreateMat( initial_quads->total , 1, CV_32FC2 );
CvMat* clusters = cvCreateMat( initial_quads->total , 1, CV_32SC1 );
CvSeq* partitioned_quads[2];
CvSeq* partitioned_boxes[2];
for(int i = 0; i < 2; i++) {
partitioned_quads[i] = cvCreateSeq( 0, sizeof(**partitioned_quads), sizeof(void*), storage );
partitioned_boxes[i] = cvCreateSeq( 0, sizeof(**partitioned_boxes), sizeof(CvBox2D), storage );
}
// set up the points sequence for cvKMeans2, using the box centers
for(int i = 0; i < initial_quads->total; i++) {
CvBox2D box = (*(CvBox2D*)cvGetSeqElem(initial_boxes, i));
cvSet1D(points, i, cvScalar(box.center.x,box.center.y));
}
// partition into two clusters: passport and colorchecker
cvKMeans2( points, 2, clusters,
cvTermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,
10, 1.0 ) );
for(int i = 0; i < initial_quads->total; i++) {
CvPoint2D32f pt = ((CvPoint2D32f*)points->data.fl)[i];
int cluster_idx = clusters->data.i[i];
cvSeqPush( partitioned_quads[cluster_idx],
cvGetSeqElem(initial_quads, i) );
cvSeqPush( partitioned_boxes[cluster_idx],
cvGetSeqElem(initial_boxes, i) );
// cvCircle(
// macbeth_img,
// cvPointFrom32f(pt),
// element_size*2,
// cvScalar(255*cluster_idx,0,255-(255*cluster_idx)),
// -1
// );
}
ColorChecker partitioned_checkers[2];
// check each of the two partitioned sets for the best colorchecker
for(int i = 0; i < 2; i++) {
partitioned_checkers[i] =
find_colorchecker(partitioned_quads[i], partitioned_boxes[i],
storage, macbeth_img, macbeth_original);
}
// use the colorchecker with the lowest error
found_colorchecker = partitioned_checkers[0].error < partitioned_checkers[1].error ?
partitioned_checkers[0] : partitioned_checkers[1];
cvReleaseMat( &points );
cvReleaseMat( &clusters );
}
else { // just one colorchecker to test
fprintf(stderr,"\n");
found_colorchecker = find_colorchecker(initial_quads, initial_boxes,
storage, macbeth_img, macbeth_original);
}
// render the found colorchecker
draw_colorchecker(found_colorchecker.values,found_colorchecker.points,macbeth_img,found_colorchecker.size);
// print out the colorchecker info
for(int y = 0; y < MACBETH_HEIGHT; y++) {
for(int x = 0; x < MACBETH_WIDTH; x++) {
CvScalar this_value = cvGet2D(found_colorchecker.values,y,x);
CvScalar this_point = cvGet2D(found_colorchecker.points,y,x);
printf("%.0f,%.0f,%.0f,%.0f,%.0f\n",
this_point.val[0],this_point.val[1],
this_value.val[2],this_value.val[1],this_value.val[0]);
}
}
printf("%0.f\n%f\n",found_colorchecker.size,found_colorchecker.error);
}
cvReleaseMemStorage( &storage );
if( macbeth_original ) cvReleaseImage( &macbeth_original );
if( adaptive ) cvReleaseImage( &adaptive );
return macbeth_img;
}
if( macbeth_img ) cvReleaseImage( &macbeth_img );
return NULL;
}
Region LocalisationPupil::getPupilRegion(int threshold){
Region reg;
CvConnectedComp **compList;
IplImage* im2;
int a,nComp;
bool fini = false;
int thresh = threshold;
int wSize = 15;
int iteration = 0;
int iterationMax = 20;
int diffWH = 50;
//init region
reg.x=0;
reg.y=0;
reg.dx=0;
reg.dy=0;
#ifdef DEBUG
cout<<"---- getpupilRegion ----"<<endl;
#endif
while( (0<thresh) && (thresh<255) && (!fini)){
im2 = cvCloneImage(im);
#ifdef DEBUG
cout<<"thresh = "<<thresh<<endl;
#endif
//filtrer moyenne
//cvSmooth( im2, im2, CV_MEDIAN, 3);
//binarisation
for(int i=0;i<((im2)->width)*((im2)->height);i++) {
a=(int)(*((im2)->imageData+i))>=0?(int)*((im2)->imageData+i):(int)(256+*((im2)->imageData+i));
if(a>=thresh)
*((im2)->imageData+i)=(char)0;
else
*((im2)->imageData+i)=(char)255;
}//for
//erosion 1
IplConvKernel* strel = cvCreateStructuringElementEx( wSize, wSize, 3, 3, CV_SHAPE_CROSS);
cvErode(im2, im2, strel);
cvReleaseStructuringElement( &strel );
#ifdef DEBUG
IplImage* im3 = cvCloneImage(im2);
char sname[20];
sprintf(sname,"s_%d_w_%d.tiff",thresh,wSize);
string _imageName = sname;
string fname;
if(param!=NULL && param->hasDebPupilRegionDir()){
fname = param->deb_Pupil_Region_Dir;
fname += _imageName;
cout<<"file name = "<<fname<<endl;
cvSaveImage(fname.c_str(), im2);
}
#endif
/*
//dilation 1
strel = cvCreateStructuringElementEx( 12, 12, 3, 3, CV_SHAPE_CROSS);
cvDilate(im2, im2, strel);
cvReleaseStructuringElement( &strel );
*/
//obtenir la region la plus grande dans l'image
compList = getLargestConnectedComps(im2,&nComp);
#ifdef DEBUG
cout<<"nComp = "<<nComp<<endl;
#endif
if(nComp<=0){
// Il y a aucune region
// Il faut augmenter le seuil et recommencer
#ifdef DEBUG
cout<<"Il y a aucune region! Augmenter le seuil et recommencer"<<endl<<endl;
#endif
thresh += 10;
fini = false;
}else{
// Verifier si tout les regions ayant le long et le large tres different
for(int i=0;i<nComp;i++){
#ifdef DEBUG
// Dessiner un regtangle representant cette region
CvPoint pt1;
CvPoint pt2;
pt1.x = compList[i]->rect.x;
pt1.y = compList[i]->rect.y;
pt2.x = compList[i]->rect.x + compList[i]->rect.width;
pt2.y = compList[i]->rect.y + compList[i]->rect.height;
cvRectangle (im3, pt1, pt2, CV_RGB(255, 255, 255), 1);
#endif
if(abs(compList[i]->rect.width-compList[i]->rect.height)<=diffWH){
fini = true;
//break;
}
}
#ifdef DEBUG
cvSaveImage(fname.c_str(), im3);
cvReleaseImage(&im3);
#endif
if(fini){
// Il y a aumoin une region ayant le long et le large comparables
// chercher une region qui est le plus similaire un cercle
#ifdef DEBUG
cout<<"Il y a aumoin une region ayant le long et le large comparables"<<endl;
#endif
int indexPupil,xc,yc,width,index,indexModel;
float maxpoint,point;
maxpoint = -100000.0f;
indexPupil = 0;
BYTE *model;
for(int i=0;i<nComp;i++){
#ifdef DEBUG
cout<<"\ti = "<<i<<"\t";
#endif
if(abs(compList[i]->rect.width-compList[i]->rect.height)<=diffWH){
width = (compList[i]->rect.width>compList[i]->rect.height?compList[i]->rect.width:compList[i]->rect.height);
model = this->initModel(width);
xc = compList[i]->rect.x + compList[i]->rect.width/2;
yc = compList[i]->rect.y + compList[i]->rect.height/2;
#ifdef DEBUG
cout<<"xc = "<<xc<<"\tyc = "<<yc<<endl;;
#endif
point = 0.0f;
for(int x=xc-width/2,indexModel=0;x<xc+width/2;x++){
for(int y=yc-width/2;y<yc+width/2;y++,indexModel++){
if(x>=0&&x<=(im2)->width&&y>=0&&y<=(im2)->height){
index = y*(im2)->width + x;
//cout<<"index="<<index<<"\tindexModel="<<indexModel;
//point += (float)((*((im2)->imageData+index)>0)&&(model[indexModel]>0)?1.0f:0.0f);
a=(int)(*((im2)->imageData+index))>=0?(int)*((im2)->imageData+index):(int)(256+*((im2)->imageData+index));
/*
if(a>0 && model[indexModel]>0){
point += 1.0f;
}
*/
if((a>0 && model[indexModel]>0)||(a<0 && model[indexModel]<0)){
point += 1.0f;
}else{
point -= 1.0f;
}
}
}
}
point /= width*width;
#ifdef DEBUG
cout<<"\tpoint = "<<point;
#endif
if(maxpoint<point){
maxpoint = point;
indexPupil = i;
#ifdef DEBUG
cout<<"\tmaxpoint = "<<maxpoint;
#endif
}
DELETE(model);
}
#ifdef DEBUG
cout<<endl;
#endif
}
reg.x = compList[indexPupil]->rect.x;
reg.y = compList[indexPupil]->rect.y;
reg.dx = compList[indexPupil]->rect.width;
reg.dy = compList[indexPupil]->rect.height;
#ifdef DEBUG
// Dessiner un regtangle representant cette region
CvPoint pt1;
CvPoint pt2;
pt1.x = reg.x;
pt1.y = reg.y;
pt2.x = reg.x + reg.dx;
pt2.y = reg.y + reg.dy;
cout<<"reg.x = "<<reg.x<<endl;
cout<<"reg.y = "<<reg.y<<endl;
cout<<"reg.dx = "<<reg.dx<<endl;
cout<<"reg.dy = "<<reg.dy<<endl;
cvRectangle (im2, pt1, pt2, CV_RGB(255, 255, 255), 1);
cout<<"file name = "<<this->filename<<endl;
cvSaveImage(this->filename.c_str(), im2);
#endif
}else{
// Tous les region ayant le long et le large tres different
// il faut diminuer le seuil, augmenter la taile de la fenetre de masque et recommencer
if(thresh>10){
thresh -= 10;
}
wSize += 1;
#ifdef DEBUG
cout<<"Tous les region ayant le long et le large tres different! Diminuer le seuil et recommencer"<<endl<<endl;
#endif
}
}
for(int i=0;i<10;i++){
DELETE(compList[i]);
}
DELETE(compList);
if(iteration++>iterationMax){
fini = true;
}
}//while
cvReleaseImage(&im2);
return reg;
}