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EDPF.cpp
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EDPF.cpp
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#include "EDPF.h"
using namespace cv;
using namespace std;
EDPF::EDPF(Mat srcImage)
:ED(srcImage, PREWITT_OPERATOR, 11, 3)
{
// Validate Edge Segments
sigma /= 2.5;
GaussianBlur(srcImage, smoothImage, Size(), sigma); // calculate kernel from sigma
validateEdgeSegments();
}
EDPF::EDPF(ED obj)
:ED(obj)
{
// Validate Edge Segments
sigma /= 2.5;
GaussianBlur(srcImage, smoothImage, Size(), sigma); // calculate kernel from sigma
validateEdgeSegments();
}
EDPF::EDPF(EDColor obj)
:ED(obj)
{
}
void EDPF::validateEdgeSegments()
{
divForTestSegment = 2.25; // Some magic number :-)
memset(edgeImg, 0, width*height); // clear edge image
H = new double[MAX_GRAD_VALUE];
memset(H, 0, sizeof(double)*MAX_GRAD_VALUE);
gradImg = ComputePrewitt3x3();
// Compute np: # of segment pieces
#if 1
// Does this underestimate the number of pieces of edge segments?
// What's the correct value?
np = 0;
for (int i = 0; i < segmentNos; i++) {
int len = (int)segmentPoints[i].size();
np += (len*(len - 1)) / 2;
} //end-for
// np *= 32;
#elif 0
// This definitely overestimates the number of pieces of edge segments
int np = 0;
for (int i = 0; i < segmentNos; i++) {
np += segmentPoints[i].size();
} //end-for
np = (np*(np - 1)) / 2;
#endif
// Validate segments
for (int i = 0; i< segmentNos; i++) {
TestSegment(i, 0, (int)segmentPoints[i].size() - 1);
} //end-for
ExtractNewSegments();
// clean space
delete[] H;
delete[] gradImg;
}
short * EDPF::ComputePrewitt3x3()
{
short *gradImg = new short[width*height];
memset(gradImg, 0, sizeof(short)*width*height);
int *grads = new int[MAX_GRAD_VALUE];
memset(grads, 0, sizeof(int)*MAX_GRAD_VALUE);
for (int i = 1; i<height - 1; i++) {
for (int j = 1; j<width - 1; j++) {
// Prewitt Operator in horizontal and vertical direction
// A B C
// D x E
// F G H
// gx = (C-A) + (E-D) + (H-F)
// gy = (F-A) + (G-B) + (H-C)
//
// To make this faster:
// com1 = (H-A)
// com2 = (C-F)
// Then: gx = com1 + com2 + (E-D) = (H-A) + (C-F) + (E-D) = (C-A) + (E-D) + (H-F)
// gy = com1 - com2 + (G-B) = (H-A) - (C-F) + (G-B) = (F-A) + (G-B) + (H-C)
//
int com1 = smoothImg[(i + 1)*width + j + 1] - smoothImg[(i - 1)*width + j - 1];
int com2 = smoothImg[(i - 1)*width + j + 1] - smoothImg[(i + 1)*width + j - 1];
int gx = abs(com1 + com2 + (smoothImg[i*width + j + 1] - smoothImg[i*width + j - 1]));
int gy = abs(com1 - com2 + (smoothImg[(i + 1)*width + j] - smoothImg[(i - 1)*width + j]));
int g = gx + gy;
gradImg[i*width + j] = g;
grads[g]++;
} // end-for
} //end-for
// Compute probability function H
int size = (width - 2)*(height - 2);
for (int i = MAX_GRAD_VALUE - 1; i>0; i--)
grads[i - 1] += grads[i];
for (int i = 0; i < MAX_GRAD_VALUE; i++)
H[i] = (double)grads[i] / ((double)size);
delete[] grads;
return gradImg;
}
//----------------------------------------------------------------------------------
// Resursive validation using half of the pixels as suggested by DMM algorithm
// We take pixels at Nyquist distance, i.e., 2 (as suggested by DMM)
//
void EDPF::TestSegment(int i, int index1, int index2)
{
int chainLen = index2 - index1 + 1;
if (chainLen < minPathLen)
return;
// Test from index1 to index2. If OK, then we are done. Otherwise, split into two and
// recursively test the left & right halves
// First find the min. gradient along the segment
int minGrad = 1 << 30;
int minGradIndex;
for (int k = index1; k <= index2; k++) {
int r = segmentPoints[i][k].y;
int c = segmentPoints[i][k].x;
if (gradImg[r*width + c] < minGrad) { minGrad = gradImg[r*width + c]; minGradIndex = k; }
} //end-for
// Compute nfa
double nfa = NFA(H[minGrad], (int)(chainLen / divForTestSegment));
if (nfa <= EPSILON) {
for (int k = index1; k <= index2; k++) {
int r = segmentPoints[i][k].y;
int c = segmentPoints[i][k].x;
edgeImg[r*width + c] = 255;
} //end-for
return;
} //end-if
// Split into two halves. We divide at the point where the gradient is the minimum
int end = minGradIndex - 1;
while (end > index1) {
int r = segmentPoints[i][end].y;
int c = segmentPoints[i][end].x;
if (gradImg[r*width + c] <= minGrad) end--;
else break;
} //end-while
int start = minGradIndex + 1;
while (start < index2) {
int r = segmentPoints[i][start].y;
int c = segmentPoints[i][start].x;
if (gradImg[r*width + c] <= minGrad) start++;
else break;
} //end-while
TestSegment(i, index1, end);
TestSegment(i, start, index2);
}
//----------------------------------------------------------------------------------------------
// After the validation of the edge segments, extracts the valid ones
// In other words, updates the valid segments' pixel arrays and their lengths
//
void EDPF::ExtractNewSegments()
{
//vector<Point> *segments = &segmentPoints[segmentNos];
vector< vector<Point> > validSegments;
int noSegments = 0;
for (int i = 0; i < segmentNos; i++) {
int start = 0;
while (start < segmentPoints[i].size()) {
while (start < segmentPoints[i].size()) {
int r = segmentPoints[i][start].y;
int c = segmentPoints[i][start].x;
if (edgeImg[r*width + c]) break;
start++;
} //end-while
int end = start + 1;
while (end < segmentPoints[i].size()) {
int r = segmentPoints[i][end].y;
int c = segmentPoints[i][end].x;
if (edgeImg[r*width + c] == 0) break;
end++;
} //end-while
int len = end - start;
if (len >= 10) {
// A new segment. Accepted only only long enough (whatever that means)
//segments[noSegments].pixels = &map->segments[i].pixels[start];
//segments[noSegments].noPixels = len;
validSegments.push_back(vector<Point>());
vector<Point> subVec(&segmentPoints[i][start], &segmentPoints[i][end]);
validSegments[noSegments] = subVec;
noSegments++;
} //end-else
start = end + 1;
} //end-while
} //end-for
// Copy to ed
segmentPoints = validSegments;
segmentNos = noSegments;
}
//---------------------------------------------------------------------------
// Number of false alarms code as suggested by Desolneux, Moisan and Morel (DMM)
//
double EDPF::NFA(double prob, int len)
{
double nfa = np;
for (int i = 0; i<len && nfa > EPSILON; i++)
nfa *= prob;
return nfa;
}