From d0c4206a165a3dd839db4c17dc077ff7f4f02d36 Mon Sep 17 00:00:00 2001 From: ishmal Date: Fri, 24 Mar 2006 17:10:34 +0000 Subject: [PATCH] change names --- src/trace/siox-segmentator.cpp | 1371 -------------------------------- src/trace/siox-segmentator.h | 396 --------- 2 files changed, 1767 deletions(-) delete mode 100644 src/trace/siox-segmentator.cpp delete mode 100644 src/trace/siox-segmentator.h diff --git a/src/trace/siox-segmentator.cpp b/src/trace/siox-segmentator.cpp deleted file mode 100644 index 31d99ca03..000000000 --- a/src/trace/siox-segmentator.cpp +++ /dev/null @@ -1,1371 +0,0 @@ -/* - Copyright 2005, 2006 by Gerald Friedland, Kristian Jantz and Lars Knipping - - Conversion to C++ for Inkscape by Bob Jamison - - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. - */ -#include "siox-segmentator.h" - -#include - -#include //for error() and trace() -#include //sqrt(), pow(), round(), etc - - -namespace org -{ -namespace siox -{ - -//######################################################################## -//## U T I L S (originally Utils.java) -//######################################################################## - -/** - * Collection of auxiliary image processing methods used by the - * SioxSegmentator mainly for postprocessing. - * - * @author G. Friedland, K. Jantz, L. Knipping - * @version 1.05 - * - * Conversion to C++ by Bob Jamison - * - */ - - -/** Caches color conversion values to speed up RGB->CIELAB conversion.*/ -static std::map RGB_TO_LAB; - -//forward decls -static void premultiplyMatrix(float alpha, float *cm, int cmSize); -//static float colordiffsq(long rgb0, long rgb1); -//static int getAlpha(long argb); -static int getRed(long rgb); -static int getGreen(long rgb); -static int getBlue(long rgb); -//static long packPixel(int a, int r, int g, int b); -static CLAB rgbToClab(long rgb); - -/** - * Applies the morphological dilate operator. - * - * Can be used to close small holes in the given confidence matrix. - * - * @param cm Confidence matrix to be processed. - * @param xres Horizontal resolution of the matrix. - * @param yres Vertical resolution of the matrix. - */ -static void dilate(float *cm, int xres, int yres) -{ - for (int y=0; ycm[idx]) - cm[idx]=cm[idx+1]; - } - } - for (int y=0; y=1; x--) { - int idx=(y*xres)+x; - if (cm[idx-1]>cm[idx]) - cm[idx]=cm[idx-1]; - } - } - for (int y=0; y cm[idx]) - cm[idx]=cm[((y+1)*xres)+x]; - } - } - for (int y=yres-1; y>=1; y--) { - for (int x=0; x cm[idx]) - cm[idx]=cm[((y-1)*xres)+x]; - } - } -} - -/** - * Applies the morphological erode operator. - * - * @param cm Confidence matrix to be processed. - * @param xres Horizontal resolution of the matrix. - * @param yres Vertical resolution of the matrix. - */ -static void erode(float *cm, int xres, int yres) -{ - for (int y=0; y=1; x--) { - int idx=(y*xres)+x; - if (cm[idx-1] < cm[idx]) - cm[idx]=cm[idx-1]; - } - } - for (int y=0; y=1; y--) { - for (int x=0; x - * In the standard case confidence matrix entries are between 0...1 and - * the weight factors sum up to 1. - * - * @param cm The matrix to be smoothed. - * @param xres Horizontal resolution of the matrix. - * @param yres Vertical resolution of the matrix. - * @param f1 Weight factor for the first pixel. - * @param f2 Weight factor for the mid-pixel. - * @param f3 Weight factor for the last pixel. - */ -static void smoothcm(float *cm, int xres, int yres, - float f1, float f2, float f3) -{ - for (int y=0; y=2; x--) { - int idx=(y*xres)+x; - cm[idx]=f3*cm[idx-2]+f2*cm[idx-1]+f1*cm[idx]; - } - } - for (int y=0; y=2; y--) { - for (int x=0; x - * Usage hint: When only comparisons between Euclidian distances without - * actual values are needed, the squared distance can be preferred - * for being faster to compute. - * - * @param p First euclidian point coordinates. - * @param pSize Length of coordinate array. - * @param q Second euclidian point coordinates. - * Dimension must not be smaller than that of p. - * Any extra dimensions will be ignored. - * @return Squared euclidian distance of p and q. - * @see #euclid - */ -static float sqrEuclidianDist(float *p, int pSize, float *q) -{ - float sum=0; - for (int i=0; i - * Usage hint: When only comparisons between Euclidian distances without - * actual values are needed, the squared distance can be preferred - * for being faster to compute. - * - * @param p CLAB value - * @param q second CLAB value - * @return Squared euclidian distance of p and q. - * @see #euclid - */ -static float sqrEuclidianDist(const CLAB &p, const CLAB &q) -{ - float sum=0; - sum += (p.C - q.C) * (p.C - q.C); - sum += (p.L - q.L) * (p.L - q.L); - sum += (p.A - q.A) * (p.A - q.A); - sum += (p.B - q.B) * (p.B - q.B); - return sum; -} - -/** - * Euclidian distance of p and q. - * - * @param p First euclidian point coordinates. - * @param pSize Length of coordinate array. - * @param q Second euclidian point coordinates. - * Dimension must not be smaller than that of p. - * Any extra dimensions will be ignored. - * @return Squared euclidian distance of p and q. - * @see #sqrEuclidianDist - */ -/* -static float euclid(float *p, int pSize, float *q) -{ - return (float)sqrt(sqrEuclidianDist(p, pSize, q)); -} -*/ - -/** - * Computes Euclidian distance of two RGB color values. - * - * @param rgb0 First color value. - * @param rgb1 Second color value. - * @return Euclidian distance between the two color values. - */ -/* -static float colordiff(long rgb0, long rgb1) -{ - return (float)sqrt(colordiffsq(rgb0, rgb1)); -} -*/ - -/** - * Computes squared euclidian distance of two RGB color values. - *

- * Note: Faster to compute than colordiff - * - * @param rgb0 First color value. - * @param rgb1 Second color value. - * @return Squared Euclidian distance between the two color values. - */ -/* -static float colordiffsq(long rgb0, long rgb1) -{ - int rDist=getRed(rgb0) - getRed(rgb1); - int gDist=getGreen(rgb0) - getGreen(rgb1); - int bDist=getBlue(rgb0) - getBlue(rgb1); - - return (float)(rDist*rDist+gDist*gDist+bDist*bDist); -} -*/ - -/** - * Averages two ARGB colors. - * - * @param argb0 First color value. - * @param argb1 Second color value. - * @return The averaged ARGB color. - */ -/* -static long average(long argb0, long argb1) -{ - long ret = packPixel( - (getAlpha(argb0) + getAlpha(argb1))/2, - (getRed(argb0) + getRed(argb1) )/2, - (getGreen(argb0) + getGreen(argb1))/2, - (getBlue(argb0) + getBlue(argb1) )/2); - return ret; -} -*/ - -/** - * Computes squared euclidian distance in CLAB space for two colors - * given as RGB values. - * - * @param rgb0 First color value. - * @param rgb1 Second color value. - * @return Squared Euclidian distance in CLAB space. - */ -static float labcolordiffsq(long rgb1, long rgb2) -{ - CLAB c1 = rgbToClab(rgb1); - CLAB c2 = rgbToClab(rgb2); - float euclid=0.0f; - euclid += (c1.L - c2.L) * (c1.L - c2.L); - euclid += (c1.A - c2.A) * (c1.A - c2.A); - euclid += (c1.B - c2.B) * (c1.B - c2.B); - return euclid; -} - - -/** - * Computes squared euclidian distance in CLAB space for two colors - * given as RGB values. - * - * @param rgb0 First color value. - * @param rgb1 Second color value. - * @return Euclidian distance in CLAB space. - */ -static float labcolordiff(long rgb0, long rgb1) -{ - return (float)sqrt(labcolordiffsq(rgb0, rgb1)); -} - - -/** - * Converts 24-bit RGB values to {l,a,b} float values. - *

- * The conversion used is decribed at - * CLAB Conversion - * for reference white D65. Note that that the conversion is computational - * expensive. Result are cached to speed up further conversion calls. - * - * @param rgb RGB color value, - * @return CLAB color value tripel. - */ -static CLAB rgbToClab(long rgb) -{ - std::map::iterator iter = RGB_TO_LAB.find(rgb); - if (iter != RGB_TO_LAB.end()) - { - CLAB res = iter->second; - return res; - } - - int R=getRed(rgb); - int G=getGreen(rgb); - int B=getBlue(rgb); - - float var_R=(R/255.0f); //R = From 0 to 255 - float var_G=(G/255.0f); //G = From 0 to 255 - float var_B=(B/255.0f); //B = From 0 to 255 - - if (var_R>0.04045) - var_R=(float) pow((var_R+0.055f)/1.055f, 2.4); - else - var_R=var_R/12.92f; - - if (var_G>0.04045) - var_G=(float) pow((var_G+0.055f)/1.055f, 2.4); - else - var_G=var_G/12.92f; - - if (var_B>0.04045) - var_B=(float) pow((var_B+0.055f)/1.055f, 2.4); - else - var_B=var_B/12.92f; - - var_R=var_R*100.0f; - var_G=var_G*100.0f; - var_B=var_B*100.0f; - - // Observer. = 2�, Illuminant = D65 - float X=var_R*0.4124f + var_G*0.3576f + var_B*0.1805f; - float Y=var_R*0.2126f + var_G*0.7152f + var_B*0.0722f; - float Z=var_R*0.0193f + var_G*0.1192f + var_B*0.9505f; - - float var_X=X/95.047f; - float var_Y=Y/100.0f; - float var_Z=Z/108.883f; - - if (var_X>0.008856f) - var_X=(float) pow(var_X, 0.3333f); - else - var_X=(7.787f*var_X)+(16.0f/116.0f); - - if (var_Y>0.008856f) - var_Y=(float) pow(var_Y, 0.3333f); - else - var_Y=(7.787f*var_Y)+(16.0f/116.0f); - - if (var_Z>0.008856f) - var_Z=(float) pow(var_Z, 0.3333f); - else - var_Z=(7.787f*var_Z)+(16.0f/116.0f); - - CLAB lab((116.0f*var_Y)-16.0f , 500.0f*(var_X-var_Y), 200.0f*(var_Y-var_Z)); - - RGB_TO_LAB[rgb] = lab; - - return lab; -} - -/** - * Converts an CLAB value to a RGB color value. - *

- * This is the reverse operation to rgbToClab. - * @param clab CLAB value. - * @return RGB value. - * @see #rgbToClab - */ -/* -static long clabToRGB(const CLAB &clab) -{ - float L=clab.L; - float a=clab.A; - float b=clab.B; - - float var_Y=(L+16.0f)/116.0f; - float var_X=a/500.0f+var_Y; - float var_Z=var_Y-b/200.0f; - - float var_yPow3=(float)pow(var_Y, 3.0); - float var_xPow3=(float)pow(var_X, 3.0); - float var_zPow3=(float)pow(var_Z, 3.0); - - if (var_yPow3>0.008856f) - var_Y=var_yPow3; - else - var_Y=(var_Y-16.0f/116.0f)/7.787f; - - if (var_xPow3>0.008856f) - var_X=var_xPow3; - else - var_X=(var_X-16.0f/116.0f)/7.787f; - - if (var_zPow3>0.008856f) - var_Z=var_zPow3; - else - var_Z=(var_Z-16.0f/116.0f)/7.787f; - - float X=95.047f * var_X; //ref_X= 95.047 Observer=2�, Illuminant=D65 - float Y=100.0f * var_Y; //ref_Y=100.000 - float Z=108.883f * var_Z; //ref_Z=108.883 - - var_X=X/100.0f; //X = From 0 to ref_X - var_Y=Y/100.0f; //Y = From 0 to ref_Y - var_Z=Z/100.0f; //Z = From 0 to ref_Y - - float var_R=(float)(var_X * 3.2406f + var_Y * -1.5372f + var_Z * -0.4986f); - float var_G=(float)(var_X * -0.9689f + var_Y * 1.8758f + var_Z * 0.0415f); - float var_B=(float)(var_X * 0.0557f + var_Y * -0.2040f + var_Z * 1.0570f); - - if (var_R>0.0031308f) - var_R=(float)(1.055f*pow(var_R, (1.0f/2.4f))-0.055f); - else - var_R=12.92f*var_R; - - if (var_G>0.0031308f) - var_G=(float)(1.055f*pow(var_G, (1.0f/2.4f))-0.055f); - else - var_G=12.92f*var_G; - - if (var_B>0.0031308f) - var_B=(float)(1.055f*pow(var_B, (1.0f/2.4f))-0.055f); - else - var_B=12.92f*var_B; - - int R = (int)lround(var_R*255.0f); - int G = (int)lround(var_G*255.0f); - int B = (int)lround(var_B*255.0f); - - return packPixel(0xFF, R, G, B); -} -*/ - -/** - * Sets the alpha byte of a pixel. - * - * Constructs alpha to values from 0 to 255. - * @param alpha Alpha value from 0 (transparent) to 255 (opaque). - * @param rgb The 24bit rgb color to be combined with the alpga value. - * @return An ARBG calor value. - */ -static long setAlpha(int alpha, long rgb) -{ - if (alpha>255) - alpha=0; - else if (alpha<0) - alpha=0; - return (alpha<<24)|(rgb&0xFFFFFF); -} - -/** - * Sets the alpha byte of a pixel. - * - * Constricts alpha to values from 0 to 255. - * @param alpha Alpha value from 0.0f (transparent) to 1.0f (opaque). - * @param rgb The 24bit rgb color to be combined with the alpga value. - * @return An ARBG calor value. - */ -static long setAlpha(float alpha, long rgb) -{ - return setAlpha((int)(255.0f*alpha), rgb); -} - -/** - * Limits the values of a,r,g,b to values from 0 to 255 and puts them - * together into an 32 bit integer. - * - * @param a Alpha part, the first byte. - * @param r Red part, the second byte. - * @param g Green part, the third byte. - * @param b Blue part, the fourth byte. - * @return A ARBG value packed to an int. - */ -/* -static long packPixel(int a, int r, int g, int b) -{ - if (a<0) - a=0; - else if (a>255) - a=255; - - if (r<0) - r=0; - else if (r>255) - r=255; - - if (g<0) - g=0; - else if (g>255) - g=255; - - if (b<0) - b=0; - else if (b>255) - b=255; - - return (a<<24)|(r<<16)|(g<<8)|b; -} -*/ - -/** - * Returns the alpha component of an ARGB value. - * - * @param argb An ARGB color value. - * @return The alpha component, ranging from 0 to 255. - */ -/* -static int getAlpha(long argb) -{ - return (argb>>24)&0xFF; -} -*/ - -/** - * Returns the red component of an (A)RGB value. - * - * @param rgb An (A)RGB color value. - * @return The red component, ranging from 0 to 255. - */ -static int getRed(long rgb) -{ - return (rgb>>16)&0xFF; -} - - -/** - * Returns the green component of an (A)RGB value. - * - * @param rgb An (A)RGB color value. - * @return The green component, ranging from 0 to 255. - */ -static int getGreen(long rgb) -{ - return (rgb>>8)&0xFF; -} - -/** - * Returns the blue component of an (A)RGB value. - * - * @param rgb An (A)RGB color value. - * @return The blue component, ranging from 0 to 255. - */ -static int getBlue(long rgb) -{ - return (rgb)&0xFF; -} - -/** - * Returns a string representation of a CLAB value. - * - * @param clab The CLAB value. - * @param clabSize Size of the CLAB value. - * @return A string representation of the CLAB value. - */ -/* -static std::string clabToString(const CLAB &clab) -{ - std::string buff; - char nbuf[60]; - snprintf(nbuf, 59, "%5.3f, %5.3f, %5.3f", clab.L, clab.A, clab.B); - buff = nbuf; - return buff; -} -*/ - -//######################################################################## -//## C O L O R S I G N A T U R E (originally ColorSignature.java) -//######################################################################## - -/** - * Representation of a color signature. - *

- * This class implements a clustering algorithm based on a modified kd-tree. - * The splitting rule is to simply divide the given interval into two equally - * sized subintervals. - * In the stageone(), approximate clusters are found by building - * up such a tree and stopping when an interval at a node has become smaller - * than the allowed cluster diameter, which is given by limits. - * At this point, clusters may be split in several nodes.
- * Therefore, in stagetwo(), nodes that belong to several clusters - * are recombined by another k-d tree clustering on the prior cluster - * centroids. To guarantee a proper level of abstraction, clusters that contain - * less than 0.01% of the pixels of the entire sample are removed. Please - * refer to the file NOTICE to get links to further documentation. - * - * @author Gerald Friedland, Lars Knipping - * @version 1.02 - * - * Conversion to C++ by Bob Jamison - * - */ - -/** - * Stage one of clustering. - * @param points float[][] the input points in LAB space - * @param depth int used for recursion, start with 0 - * @param clusters ArrayList an Arraylist to store the clusters - * @param limits float[] the cluster diameters - */ -static void stageone(std::vector &points, - int depth, - std::vector< std::vector > &clusters, - float *limits) -{ - if (points.size() < 1) - return; - - int dims=3; - int curdim=depth%dims; - float min = 0.0f; - float max = 0.0f; - if (curdim == 0) - { - min=points[0].C; - max=points[0].C; - // find maximum and minimum - for (unsigned int i=1; ipoints[i].C) - min=points[i].C; - if (maxpoints[i].L) - min=points[i].L; - if (maxpoints[i].A) - min=points[i].A; - if (maxpoints[i].B) - min=points[i].B; - if (maxlimits[curdim]) { // Split according to Rubner-Rule - // split - float pivotvalue=((max-min)/2.0f)+min; - - std::vector smallerpoints; // allocate mem - std::vector biggerpoints; - - for (unsigned int i=0; i &points, - int depth, - std::vector< std::vector > &clusters, - float *limits, int total, float threshold) -{ - if (points.size() < 1) - return; - - int curdim=depth%3; // without cardinality - float min = 0.0f; - float max = 0.0f; - if (curdim == 0) - { - min=points[0].L; - max=points[0].L; - // find maximum and minimum - for (unsigned int i=1; ipoints[i].L) - min=points[i].L; - if (maxpoints[i].A) - min=points[i].A; - if (maxpoints[i].B) - min=points[i].B; - if (maxlimits[curdim]) { // Split according to Rubner-Rule - // split - float pivotvalue=((max-min)/2.0f)+min; - - std::vector smallerpoints; // allocate mem - std::vector biggerpoints; - - for (unsigned int i=0; i=threshold) { - CLAB point; - for (unsigned int i=0; i newCluster; - newCluster.push_back(point); - clusters.push_back(newCluster); - } - } -} - -/** - * Create a color signature for the given set of pixels. - * @param input float[][] a set of pixels in LAB space - * @param length int the number of pixels that should be processed from the input - * @param limits float[] the cluster diameters for each dimension - * @param threshold float the abstraction threshold - * @return float[][] a color siganture containing cluster centroids in LAB space - */ -static std::vector createSignature(std::vector &input, - float *limits, float threshold) -{ - std::vector< std::vector > clusters1; - std::vector< std::vector > clusters2; - - stageone(input, 0, clusters1, limits); - - std::vector centroids; - for (unsigned int i=0; i cluster = clusters1[i]; - CLAB centroid; // +1 for the cardinality - for (unsigned int k=0; k see paper by tomasi - - std::vector res; - for (unsigned int i=0 ; i=FOREGROUND_CONFIDENCE) - knownFg.push_back(rgbToClab(image[i])); - } - - bgSignature = createSignature(knownBg, limits, BACKGROUND_CONFIDENCE); - fgSignature = createSignature(knownFg, limits, BACKGROUND_CONFIDENCE); - - if (bgSignature.size() < 1) { - // segmentation impossible - return false; - } - - // classify using color signatures, - // classification cached in hashmap for drb and speedup purposes - for (int i=0; i=FOREGROUND_CONFIDENCE) { - cm[i]=CERTAIN_FOREGROUND_CONFIDENCE; - continue; - } - if (cm[i]>BACKGROUND_CONFIDENCE) { - bool isBackground=true; - std::map::iterator iter = hs.find(i); - Tupel tupel(0.0f, 0, 0.0f, 0); - if (iter == hs.end()) { - CLAB lab = rgbToClab(image[i]); - float minBg = sqrEuclidianDist(lab, bgSignature[0]); - int minIndex=0; - for (unsigned int j=1; j=UNKNOWN_REGION_CONFIDENCE) { - cm[i]=CERTAIN_FOREGROUND_CONFIDENCE; - } else { - cm[i]=CERTAIN_BACKGROUND_CONFIDENCE; - } - } - - keepOnlyLargeComponents(cm, cmSize, UNKNOWN_REGION_CONFIDENCE, sizeFactorToKeep); - fillColorRegions(cm, cmSize, image); - dilate(cm, imgWidth, imgHeight); - - segmentated=true; - return true; -} - - - -void SioxSegmentator::keepOnlyLargeComponents(float *cm, int cmSize, - float threshold, - double sizeFactorToKeep) -{ - int idx = 0; - for (int i=0 ; i labelSizes; - for (int i=0 ; i=threshold) { - regionCount=depthFirstSearch(cm, i, threshold, curlabel++); - labelSizes.push_back(regionCount); - } - - if (regionCount>maxregion) { - maxregion=regionCount; - maxblob=curlabel-1; - } - } - - for (int i=0 ; i pixelsToVisit; - int componentSize=0; - if (labelField[i]==-1 && cm[i]>=threshold) { // label #i - labelField[i] = curLabel; - ++componentSize; - pixelsToVisit.push_back(i); - } - while (pixelsToVisit.size() > 0) { - int pos=pixelsToVisit[pixelsToVisit.size()-1]; - pixelsToVisit.erase(pixelsToVisit.end()-1); - int x=pos%imgWidth; - int y=pos/imgWidth; - // check all four neighbours - int left = pos-1; - if (x-1>=0 && labelField[left]==-1 && cm[left]>=threshold) { - labelField[left]=curLabel; - ++componentSize; - pixelsToVisit.push_back(left); - } - int right = pos+1; - if (x+1=threshold) { - labelField[right]=curLabel; - ++componentSize; - pixelsToVisit.push_back(right); - } - int top = pos-imgWidth; - if (y-1>=0 && labelField[top]==-1 && cm[top]>=threshold) { - labelField[top]=curLabel; - ++componentSize; - pixelsToVisit.push_back(top); - } - int bottom = pos+imgWidth; - if (y+1=threshold) { - labelField[bottom]=curLabel; - ++componentSize; - pixelsToVisit.push_back(bottom); - } - } - return componentSize; -} - -void SioxSegmentator::subpixelRefine(int x, int y, int brushmode, - float threshold, float *cf, int brushsize) -{ - subpixelRefine(x-brushsize, y-brushsize, - 2*brushsize, 2*brushsize, - brushmode, threshold, cf); -} - - -bool SioxSegmentator::subpixelRefine(int xa, int ya, int dx, int dy, - int brushmode, - float threshold, float *cf) -{ - if (!segmentated) { - error("no segmentation yet"); - return false; - } - - int x0 = (xa > 0) ? xa : 0; - int y0 = (ya > 0) ? ya : 0; - - int xTo = (imgWidth - 1 < xa+dx ) ? imgWidth-1 : xa+dx; - int yTo = (imgHeight - 1 < ya+dy ) ? imgHeight-1 : ya+dy; - - for (int ey=y0; ey::iterator iter = hs.find(val); - if (iter != hs.end()) { - minDistBg=(float) sqrt((float)iter->second.minBgDist); - minDistFg=(float) sqrt((float)iter->second.minFgDist); - } else { - continue; - } - if (ADD_EDGE == brushmode) { // handle adder - if (cf[ey*imgWidth+ex]FOREGROUND_CONFIDENCE) { - // foreground, we want to take something away - float alpha; - if (minDistBg==0) { - alpha=CERTAIN_BACKGROUND_CONFIDENCE; - } else { - alpha=CERTAIN_FOREGROUND_CONFIDENCE- - (minDistFg/minDistBg < CERTAIN_FOREGROUND_CONFIDENCE) ? // more background -> >1 - minDistFg/minDistBg : CERTAIN_FOREGROUND_CONFIDENCE; - // bg = gf -> 1 - // more fg -> <1 - } - if (alpha pixelsToVisit; - for (int i=0; i 0) { - int pos=pixelsToVisit[pixelsToVisit.size()-1]; - pixelsToVisit.erase(pixelsToVisit.end()-1); - int x=pos%imgWidth; - int y=pos/imgWidth; - // check all four neighbours - int left = pos-1; - if (x-1>=0 && labelField[left]==-1 - && labcolordiff(image[left], origColor)<1.0) { - labelField[left]=curLabel; - cm[left]=CERTAIN_FOREGROUND_CONFIDENCE; - // ++componentSize; - pixelsToVisit.push_back(left); - } - int right = pos+1; - if (x+1=0 && labelField[top]==-1 - && labcolordiff(image[top], origColor)<1.0) { - labelField[top]=curLabel; - cm[top]=CERTAIN_FOREGROUND_CONFIDENCE; - // ++componentSize; - pixelsToVisit.push_back(top); - } - int bottom = pos+imgWidth; - if (y+1maxRegion) { - // maxRegion=componentSize; - //} - } -} - - - - - - - - - - - - - - -} //namespace siox -} //namespace org - - - diff --git a/src/trace/siox-segmentator.h b/src/trace/siox-segmentator.h deleted file mode 100644 index 4d92a9182..000000000 --- a/src/trace/siox-segmentator.h +++ /dev/null @@ -1,396 +0,0 @@ -#ifndef __SIOX_SEGMENTATOR_H__ -#define __SIOX_SEGMENTATOR_H__ -/* - Copyright 2005, 2006 by Gerald Friedland, Kristian Jantz and Lars Knipping - - Conversion to C++ for Inkscape by Bob Jamison - - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. - */ - -#include -#include - -namespace org -{ -namespace siox -{ - -/** - * Image segmentator based on - *SIOX: Simple Interactive Object Extraction. - *

- * To segmentate an image one has to perform the following steps. - *

  1. Construct an instance of SioxSegmentator. - *
  2. Create a confidence matrix, where each entry marks its - * corresponding image pixel to belong to the foreground, to the - * background, or being of unknown type. - *
  3. Call segmentate on the image with the confidence - * matrix. This stores the result as new foreground confidence into - * the confidence matrix, with each entry being either - * zero (CERTAIN_BACKGROUND_CONFIDENCE) or one - * (CERTAIN_FOREGROUND_CONFIDENCE). - *
  4. Optionally call subpixelRefine to areas - * where pixels contain both foreground and background (e.g. - * object borders or highly detailed features like flowing hairs). - * The pixel are then assigned confidence values bwetween zero and - * one to give them a measure of "foregroundness". - * This step may be repeated as often as needed. - *
- *

- * For algorithm documentation refer to - * G. Friedland, K. Jantz, L. Knipping, R. Rojas: - * Image Segmentation by Uniform Color Clustering - * -- Approach and Benchmark Results, - * Technical Report B-05-07, - * Department of Computer Science, Freie Universitaet Berlin, June 2005.
- *

- * See http://www.siox.org for more information.
- *

- * Algorithm idea by Gerald Friedland. - * - * @author Gerald Friedland, Kristian Jantz, Lars Knipping - * @version 1.12 - */ - -/** - * Helper class for storing the minimum distances to a cluster centroid - * in background and foreground and the index to the centroids in each - * signature for a given color. - */ -class Tupel { -public: - - Tupel() - { - minBgDist = 0.0f; - indexMinBg = 0; - minFgDist = 0.0f; - indexMinFg = 0; - } - Tupel(float minBgDistArg, long indexMinBgArg, - float minFgDistArg, long indexMinFgArg) - { - minBgDist = minBgDistArg; - indexMinBg = indexMinBgArg; - minFgDist = minFgDistArg; - indexMinFg = indexMinFgArg; - } - Tupel(const Tupel &other) - { - minBgDist = other.minBgDist; - indexMinBg = other.indexMinBg; - minFgDist = other.minFgDist; - indexMinFg = other.indexMinFg; - } - Tupel &operator=(const Tupel &other) - { - minBgDist = other.minBgDist; - indexMinBg = other.indexMinBg; - minFgDist = other.minFgDist; - indexMinFg = other.indexMinFg; - return *this; - } - virtual ~Tupel() - {} - - float minBgDist; - long indexMinBg; - float minFgDist; - long indexMinFg; - - }; - - -class CLAB -{ -public: - CLAB() - { - C = L = A = B = 0.0f; - } - CLAB(float lArg, float aArg, float bArg) - { - C = 0.0f; - L = lArg; - A = aArg; - B = bArg; - } - CLAB(const CLAB &other) - { - C = other.C; - L = other.L; - A = other.A; - B = other.B; - } - CLAB &operator=(const CLAB &other) - { - C = other.C; - L = other.L; - A = other.A; - B = other.B; - return *this; - } - virtual ~CLAB() - {} - - float C; - float L; - float A; - float B; -}; - - -class SioxSegmentator -{ -public: - - /** Confidence corresponding to a certain foreground region (equals one). */ - static const float CERTAIN_FOREGROUND_CONFIDENCE=1.0f; - - /** Confidence for a region likely being foreground.*/ - static const float FOREGROUND_CONFIDENCE=0.8f; - - /** Confidence for foreground or background type being equally likely.*/ - static const float UNKNOWN_REGION_CONFIDENCE=0.5f; - - /** Confidence for a region likely being background.*/ - static const float BACKGROUND_CONFIDENCE=0.1f; - - /** Confidence corresponding to a certain background reagion (equals zero). */ - static const float CERTAIN_BACKGROUND_CONFIDENCE=0.0f; - - - /** - * Constructs a SioxSegmentator Object to be used for image segmentation. - * - * @param w X resolution of the image to be segmentated. - * @param h Y resolution of the image to be segmentated. - * @param limits Size of the cluster on LAB axises. - * If null, the default value {0.64f,1.28f,2.56f} - * is used. - */ - SioxSegmentator(int w, int h, float *limitsArg, int limitsSize); - - /** - * Destructor - */ - virtual ~SioxSegmentator(); - - - /** - * Segmentates the given image with information from the confidence - * matrix. - *

- * The confidence entries of BACKGROUND_CONFIDENCE or less - * are mark known background pixel for the segmentation, those - * of at least FOREGROUND_CONFIDENCE mark known - * foreground pixel for the segmentation. Any other entry is treated - * as region of unknown affiliation. - *

- * As result, each pixel is classified either as foregroound or - * background, stored back into its cm entry as confidence - * CERTAIN_FOREGROUND_CONFIDENCE or - * CERTAIN_BACKGROUND_CONFIDENCE. - * - * @param image Pixel data of the image to be segmentated. - * Every integer represents one ARGB-value. - * @param imageSize number of values in image - * @param cm Confidence matrix specifying the probability of an image - * belonging to the foreground before and after the segmentation. - * @param smoothness Number of smoothing steps in the post processing. - * @param sizeFactorToKeep Segmentation retains the largest connected - * foreground component plus any component with size at least - * sizeOfLargestComponent/sizeFactorToKeep. - * @return true if the segmentation algorithm succeeded, - * false if segmentation is impossible - */ - bool segmentate(long *image, int imageSize, - float *cm, int cmSize, - int smoothness, double sizeFactorToKeep); - - /** - * Clears given confidence matrix except entries for the largest connected - * component and every component with - * size*sizeFactorToKeep >= sizeOfLargestComponent. - * - * @param cm Confidence matrix to be analysed - * @param threshold Pixel visibility threshold. - * Exactly those cm entries larger than threshold are considered - * to be a "visible" foreground pixel. - * @param sizeFactorToKeep This method keeps the largest connected - * component plus any component with size at least - * sizeOfLargestComponent/sizeFactorToKeep. - */ - void keepOnlyLargeComponents(float *cm, int cmSize, - float threshold, - double sizeFactorToKeep); - - /** - * Depth first search pixels in a foreground component. - * - * @param cm confidence matrix to be searched. - * @param i starting position as index to confidence matrix. - * @param threshold defines the minimum value at which a pixel is - * considered foreground. - * @param curlabel label no of component. - * @return size in pixel of the component found. - */ - int depthFirstSearch(float *cm, int i, float threshold, int curLabel); - - /** - * Refines the classification stored in the confidence matrix by modifying - * the confidences for regions which have characteristics to both - * foreground and background if they fall into the specified square. - *

- * The can be used in displaying the image by assigning the alpha values - * of the pixels according to the confidence entries. - *

- * In the algorithm descriptions and examples GUIs this step is referrered - * to as Detail Refinement (Brush). - * - * @param x Horizontal coordinate of the squares center. - * @param y Vertical coordinate of the squares center. - * @param brushmode Mode of the refinement applied, ADD_EDGE - * or SUB_EDGE. Add mode only modifies pixels - * formerly classified as background, sub mode only those - * formerly classified as foreground. - * @param threshold Threshold for the add and sub refinement, deciding - * at the confidence level to stop at. - * @param cf The confidence matrix to modify, generated by - * segmentate, possibly already refined by privious - * calls to subpixelRefine. - * @param brushsize Halfed diameter of the square shaped brush. - * - * @see #segmentate - */ - void SioxSegmentator::subpixelRefine(int x, int y, int brushmode, - float threshold, float *cf, int brushsize); - - /** - * Refines the classification stored in the confidence matrix by modifying - * the confidences for regions which have characteristics to both - * foreground and background if they fall into the specified area. - *

- * The can be used in displaying the image by assigning the alpha values - * of the pixels according to the confidence entries. - *

- * In the algorithm descriptions and examples GUIs this step is referrered - * to as Detail Refinement (Brush). - * - * @param area Area in which the reworking of the segmentation is - * applied to. - * @param brushmode Mode of the refinement applied, ADD_EDGE - * or SUB_EDGE. Add mode only modifies pixels - * formerly classified as background, sub mode only those - * formerly classified as foreground. - * @param threshold Threshold for the add and sub refinement, deciding - * at the confidence level to stop at. - * @param cf The confidence matrix to modify, generated by - * segmentate, possibly already refined by privious - * calls to subpixelRefine. - * - * @see #segmentate - */ - bool SioxSegmentator::subpixelRefine(int xa, int ya, int dx, int dy, - int brushmode, - float threshold, float *cf); - /** - * A region growing algorithms used to fill up the confidence matrix - * with CERTAIN_FOREGROUND_CONFIDENCE for corresponding - * areas of equal colors. - *

- * Basically, the method works like the Magic Wand with a - * tolerance threshold of zero. - * - * @param cm confidence matrix to be searched - * @param image image to be searched - */ - void fillColorRegions(float *cm, int cmSize, long *image); - -private: - - /** - * Prevent this from being used - */ - SioxSegmentator(); - - /** error logging **/ - void error(char *format, ...); - - /** trace logging **/ - void trace(char *format, ...); - - typedef enum - { - ADD_EDGE, /** Add mode for the subpixel refinement. */ - SUB_EDGE /** Subtract mode for the subpixel refinement. */ - } BrushMode; - - // instance fields: - - /** Horizontal resolution of the image to be segmentated. */ - int imgWidth; - - /** Vertical resolution of the image to be segmentated. */ - int imgHeight; - - /** Stores component label (index) by pixel it belongs to. */ - int *labelField; - - /** - * LAB color values of pixels that are definitly known background. - * Entries are of form {l,a,b}. - */ - std::vector knownBg; - - /** - * LAB color values of pixels that are definitly known foreground. - * Entries are of form {l,a,b}. - */ - std::vector knownFg; - - /** Holds background signature (a characteristic subset of the bg.) */ - std::vector bgSignature; - - /** Holds foreground signature (a characteristic subset of the fg).*/ - std::vector fgSignature; - - /** Size of cluster on lab axis. */ - float *limits; - - /** Maximum distance of two lab values. */ - float clusterSize; - - /** - * Stores Tupels for fast access to nearest background/foreground pixels. - */ - std::map hs; - - /** Size of the biggest blob.*/ - int regionCount; - - /** Copy of the original image, needed for detail refinement. */ - long *origImage; - long origImageSize; - - /** A flag that stores if the segmentation algorithm has already ran.*/ - bool segmentated; - -}; - -} //namespace siox -} //namespace org - -#endif /* __SIOX_SEGMENTATOR_H__ */ - -- 2.30.2