/*
* 用于对图像数据的处理
* */
JNIEXPORT jint JNICALL Java_com_nova_novapro_MainActivity_TransImage
(JNIEnv *env, jobject obj)
{
char* source = "/sdcard/capture/1.bmp";
char* dest = "/sdcard/capture/dest1.bmp";
int ret;
int arrage;
unsigned char* tmpBuffer;
unsigned char* locationMark;
RegionInfo regionInfo;
regionInfo.xres = 32;
regionInfo.yres = 16;
int pic_size = picInfo.xres * picInfo.yres * picInfo.bpp;
LOGD("pic_size=%d\n",pic_size);
//为tmpBuffer分配内存
tmpBuffer = (unsigned char*)malloc(pic_size);
if(tmpBuffer == NULL){
LOGD("malloc date error!");
}
//将bmp图像中的数据读取到tmpbuffer中
ret = ReadBmp2Buffer(source,dest,&picInfo,tmpBuffer);
//进行一个RGB到灰度值的转换
ret = RGB2GREY(&picInfo,tmpBuffer);
//获取图像的二值化阈值
arrage = GetThreshold(&picInfo,tmpBuffer);
LOGD("Threshold=%d\n",arrage);
//将图片中小于arrage的数据设置为0 二值化
Thresholding(arrage,&picInfo,tmpBuffer);
//从图像中心开始对图像进行定位操作
ret = locataImage(&picInfo,tmpBuffer,®ionInfo);
//将date数据保存到bmp中
ret = saveDate2BMP(&picInfo,tmpBuffer,dest);
free(tmpBuffer);
return ret;
}
cv::Mat process(int newSize) {
image = Thresholding(image).transform();
// cut egdes:
for (int i = 0; i < image.rows; i ++) {
if (!processRow(i)) {
break;
}
}
for (int i = image.rows - 1; i >= 0; i --) {
if (!processRow(i)) {
break;
}
}
for (int i = 0; i < image.cols; i ++) {
if (!processCol(i)) {
break;
}
}
for (int i = image.cols - 1; i >= 0; i --) {
if (!processCol(i)) {
break;
}
}
for (int i = 0; i < used.size(); i ++)
for (int j = 0; j < used[i].size(); j ++)
used[i][j] = 0;
int L = 1;
for (int i = 0; i < image.rows; i ++)
for (int j = 0; j < image.cols; j ++)
if (image.at<uchar>(i, j) == BLACK && used[i][j] == 0) {
dfs(i, j, L);
L ++;
}
std::map<int,int> cnt;
for (int i = 0; i < image.rows; i ++)
for (int j = 0; j < image.cols; j ++)
if (used[i][j] != 0)
cnt[used[i][j]] ++;
int max_value = 0;
int best_comp;
for (std::map<int,int>::iterator it = cnt.begin(); it != cnt.end(); it ++)
if (it->second > max_value) {
max_value = it->second;
best_comp = it->first;
}
for (int i = 0; i < image.rows; i ++)
for (int j = 0; j < image.cols; j ++)
if (used[i][j] != best_comp) {
image.at<uchar>(i,j) = WHITE;
}
int minRow = image.rows;
int maxRow = -1;
int minCol = image.cols;
int maxCol = -1;
for (int i = 0; i < image.rows; i ++)
for (int j = 0; j < image.cols; j ++)
if (image.at<uchar>(i,j) == BLACK) {
minRow = std::min(minRow, i);
maxRow = std::max(maxRow, i);
minCol = std::min(minCol, j);
maxCol = std::max(maxCol, j);
}
int X = minCol;
int Y = minRow;
int W = maxCol - minCol + 1;
int H = maxRow - minRow + 1;
int X0 = X - std::max(0, H - W) / 2;
int Y0 = Y - std::max(0, W - H) / 2;
try {
image = Image::getSubMatrix(image, X0, Y0, std::max(W, H), std::max(W,H));
} catch (...) {
}
cv::Mat newImage;
cv::resize(image, newImage, cv::Size(newSize, newSize));
newImage = Thresholding(newImage).transform();
return newImage;
}
