/*!
* \brief pixColorSegment()
*
* \param[in] pixs 32 bpp; 24-bit color
* \param[in] maxdist max euclidean dist to existing cluster
* \param[in] maxcolors max number of colors allowed in first pass
* \param[in] selsize linear size of sel for closing to remove noise
* \param[in] finalcolors max number of final colors allowed after 4th pass
* \param[in] debugflag 1 for debug output; 0 otherwise
* \return pixd 8 bit with colormap, or NULL on error
*
* <pre>
* Color segmentation proceeds in four phases:
*
* Phase 1: pixColorSegmentCluster()
* The image is traversed in raster order. Each pixel either
* becomes the representative for a new cluster or is assigned to an
* existing cluster. Assignment is greedy. The data is stored in
* a colormapped image. Three auxiliary arrays are used to hold
* the colors of the representative pixels, for fast lookup.
* The average color in each cluster is computed.
*
* Phase 2. pixAssignToNearestColor()
* A second non-greedy clustering pass is performed, where each pixel
* is assigned to the nearest cluster average. We also keep track
* of how many pixels are assigned to each cluster.
*
* Phase 3. pixColorSegmentClean()
* For each cluster, starting with the largest, do a morphological
* closing to eliminate small components within larger ones.
*
* Phase 4. pixColorSegmentRemoveColors()
* Eliminate all colors except the most populated 'finalcolors'.
* Then remove unused colors from the colormap, and reassign those
* pixels to the nearest remaining cluster, using the original pixel values.
*
* Notes:
* (1) The goal is to generate a small number of colors.
* Typically this would be specified by 'finalcolors',
* a number that would be somewhere between 3 and 6.
* The parameter 'maxcolors' specifies the maximum number of
* colors generated in the first phase. This should be
* larger than finalcolors, perhaps twice as large.
* If more than 'maxcolors' are generated in the first phase
* using the input 'maxdist', the distance is repeatedly
* increased by a multiplicative factor until the condition
* is satisfied. The implicit relation between 'maxdist'
* and 'maxcolors' is thus adjusted programmatically.
* (2) As a very rough guideline, given a target value of 'finalcolors',
* here are approximate values of 'maxdist' and 'maxcolors'
* to start with:
*
* finalcolors maxcolors maxdist
* ----------- --------- -------
* 3 6 100
* 4 8 90
* 5 10 75
* 6 12 60
*
* For a given number of finalcolors, if you use too many
* maxcolors, the result will be noisy. If you use too few,
* the result will be a relatively poor assignment of colors.
* </pre>
*/
PIX *
pixColorSegment(PIX *pixs,
l_int32 maxdist,
l_int32 maxcolors,
l_int32 selsize,
l_int32 finalcolors,
l_int32 debugflag)
{
l_int32 *countarray;
PIX *pixd;
PROCNAME("pixColorSegment");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("must be rgb color", procName, NULL);
/* Phase 1; original segmentation */
pixd = pixColorSegmentCluster(pixs, maxdist, maxcolors, debugflag);
if (!pixd)
return (PIX *)ERROR_PTR("pixd not made", procName, NULL);
if (debugflag) {
lept_mkdir("lept/segment");
pixWriteDebug("/tmp/lept/segment/colorseg1.png", pixd, IFF_PNG);
}
/* Phase 2; refinement in pixel assignment */
if ((countarray = (l_int32 *)LEPT_CALLOC(256, sizeof(l_int32))) == NULL) {
pixDestroy(&pixd);
return (PIX *)ERROR_PTR("countarray not made", procName, NULL);
}
pixAssignToNearestColor(pixd, pixs, NULL, LEVEL_IN_OCTCUBE, countarray);
if (debugflag)
pixWriteDebug("/tmp/lept/segment/colorseg2.png", pixd, IFF_PNG);
/* Phase 3: noise removal by separately closing each color */
pixColorSegmentClean(pixd, selsize, countarray);
LEPT_FREE(countarray);
if (debugflag)
pixWriteDebug("/tmp/lept/segment/colorseg3.png", pixd, IFF_PNG);
/* Phase 4: removal of colors with small population and
* reassignment of pixels to remaining colors */
pixColorSegmentRemoveColors(pixd, pixs, finalcolors);
return pixd;
}
/*!
* pixColorSegment()
*
* Input: pixs (32 bpp; 24-bit color)
* maxdist (max euclidean dist to existing cluster)
* maxcolors (max number of colors allowed in first pass)
* selsize (linear size of sel for closing to remove noise)
* finalcolors (max number of final colors allowed after 4th pass)
* Return: pixd (8 bit with colormap), or null on error
*
* Color segmentation proceeds in four phases:
*
* Phase 1: pixColorSegmentCluster()
* The image is traversed in raster order. Each pixel either
* becomes the representative for a new cluster or is assigned to an
* existing cluster. Assignment is greedy. The data is stored in
* a colormapped image. Three auxiliary arrays are used to hold
* the colors of the representative pixels, for fast lookup.
* The average color in each cluster is computed.
*
* Phase 2. pixAssignToNearestColor()
* A second (non-greedy) clustering pass is performed, where each pixel
* is assigned to the nearest cluster (average). We also keep track
* of how many pixels are assigned to each cluster.
*
* Phase 3. pixColorSegmentClean()
* For each cluster, starting with the largest, do a morphological
* closing to eliminate small components within larger ones.
*
* Phase 4. pixColorSegmentRemoveColors()
* Eliminate all colors except the most populated 'finalcolors'.
* Then remove unused colors from the colormap, and reassign those
* pixels to the nearest remaining cluster, using the original pixel values.
*
* Notes:
* (1) The goal is to generate a small number of colors.
* Typically this would be specified by 'finalcolors',
* a number that would be somewhere between 3 and 6.
* The parameter 'maxcolors' specifies the maximum number of
* colors generated in the first phase. This should be
* larger than finalcolors, perhaps twice as large.
* If more than 'maxcolors' are generated in the first phase
* using the input 'maxdist', the distance is repeatedly
* increased by a multiplicative factor until the condition
* is satisfied. The implicit relation between 'maxdist'
* and 'maxcolors' is thus adjusted programmatically.
* (2) As a very rough guideline, given a target value of 'finalcolors',
* here are approximate values of 'maxdist' and 'maxcolors'
* to start with:
*
* finalcolors maxcolors maxdist
* ----------- --------- -------
* 3 6 100
* 4 8 90
* 5 10 75
* 6 12 60
*
* For a given number of finalcolors, if you use too many
* maxcolors, the result will be noisy. If you use too few,
* the result will be a relatively poor assignment of colors.
*/
PIX *
pixColorSegment(PIX *pixs,
l_int32 maxdist,
l_int32 maxcolors,
l_int32 selsize,
l_int32 finalcolors)
{
l_int32 *countarray;
PIX *pixd;
PROCNAME("pixColorSegment");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 32)
return (PIX *)ERROR_PTR("must be rgb color", procName, NULL);
/* Phase 1; original segmentation */
if ((pixd = pixColorSegmentCluster(pixs, maxdist, maxcolors)) == NULL)
return (PIX *)ERROR_PTR("pixt1 not made", procName, NULL);
/* pixWrite("junkpixd1", pixd, IFF_PNG); */
/* Phase 2; refinement in pixel assignment */
if ((countarray = (l_int32 *)CALLOC(256, sizeof(l_int32))) == NULL)
return (PIX *)ERROR_PTR("countarray not made", procName, NULL);
pixAssignToNearestColor(pixd, pixs, NULL, LEVEL_IN_OCTCUBE, countarray);
/* pixWrite("junkpixd2", pixd, IFF_PNG); */
/* Phase 3: noise removal by separately closing each color */
pixColorSegmentClean(pixd, selsize, countarray);
/* pixWrite("junkpixd3", pixd, IFF_PNG); */
FREE(countarray);
/* Phase 4: removal of colors with small population and
* reassignment of pixels to remaining colors */
pixColorSegmentRemoveColors(pixd, pixs, finalcolors);
return pixd;
}
