551 lines
17 KiB
C++
551 lines
17 KiB
C++
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/*
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FAST-EDGE
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Copyright (c) 2009 Benjamin C. Haynor
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Permission is hereby granted, free of charge, to any person
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obtaining a copy of this software and associated documentation
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files (the "Software"), to deal in the Software without
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restriction, including without limitation the rights to use,
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copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the
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Software is furnished to do so, subject to the following
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conditions:
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The above copyright notice and this permission notice shall be
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included in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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OTHER DEALINGS IN THE SOFTWARE.
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*/
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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#include <math.h>
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#include <time.h>
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#include "fast-edge.h"
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#define LOW_THRESHOLD_PERCENTAGE 0.8 // percentage of the high threshold value that the low threshold shall be set at
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#define PI 3.14159265
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#define HIGH_THRESHOLD_PERCENTAGE 0.10 // percentage of pixels that meet the high threshold - for example 0.15 will ensure that at least 15% of edge pixels are considered to meet the high threshold
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#define min(X,Y) ((X) < (Y) ? (X) : (Y))
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#define max(X,Y) ((X) < (Y) ? (Y) : (X))
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namespace ocr{
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/*
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CANNY EDGE DETECT
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DOES NOT PERFORM NOISE REDUCTION - PERFORM NOISE REDUCTION PRIOR TO USE
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Noise reduction omitted, as some applications benefit from morphological operations such as opening or closing as opposed to Gaussian noise reduction
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If your application always takes the same size input image, uncomment the definitions of WIDTH and HEIGHT in the header file and define them to the size of your input image,
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otherwise the required intermediate arrays will be dynamically allocated.
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If WIDTH and HEIGHT are defined, the arrays will be allocated in the compiler directive that follows:
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*/
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#ifdef WIDTH
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int g[WIDTH * HEIGHT], dir[WIDTH * HEIGHT] = {0};
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unsigned char img_scratch_data[WIDTH * HEIGHT] = {0};
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#endif
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void canny_edge_detect(struct image * img_in, struct image * img_out) {
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struct image img_scratch;
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int high, low;
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#ifndef WIDTH
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int * g = (int*)calloc(static_cast<size_t>(img_in->width*img_in->height), sizeof(int));
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int * dir = (int*)calloc(static_cast<size_t>(img_in->width*img_in->height), sizeof(int));
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unsigned char * img_scratch_data = (unsigned char*)calloc(static_cast<size_t>(img_in->width*img_in->height), sizeof(char));
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#endif
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img_scratch.width = img_in->width;
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img_scratch.height = img_in->height;
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img_scratch.pixel_data = img_scratch_data;
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calc_gradient_sobel(img_in, g, dir);
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//printf("*** performing non-maximum suppression ***\n");
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non_max_suppression(&img_scratch, g, dir);
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estimate_threshold(&img_scratch, &high, &low);
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hysteresis(high, low, &img_scratch, img_out);
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#ifndef WIDTH
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free(g);
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free(dir);
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free(img_scratch_data);
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#endif
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}
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/*
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GAUSSIAN_NOISE_ REDUCE
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apply 5x5 Gaussian convolution filter, shrinks the image by 4 pixels in each direction, using Gaussian filter found here:
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http://en.wikipedia.org/wiki/Canny_edge_detector
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*/
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void gaussian_noise_reduce(struct image * img_in, struct image * img_out)
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{
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#ifdef CLOCK
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clock_t start = clock();
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#endif
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int w, h, x, y, max_x, max_y;
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w = img_in->width;
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h = img_in->height;
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img_out->width = w;
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img_out->height = h;
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max_x = w - 2;
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max_y = w * (h - 2);
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for (y = w * 2; y < max_y; y += w) {
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for (x = 2; x < max_x; x++) {
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img_out->pixel_data[x + y] = (2 * img_in->pixel_data[x + y - 2 - w - w] +
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4 * img_in->pixel_data[x + y - 1 - w - w] +
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5 * img_in->pixel_data[x + y - w - w] +
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4 * img_in->pixel_data[x + y + 1 - w - w] +
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2 * img_in->pixel_data[x + y + 2 - w - w] +
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4 * img_in->pixel_data[x + y - 2 - w] +
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9 * img_in->pixel_data[x + y - 1 - w] +
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12 * img_in->pixel_data[x + y - w] +
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9 * img_in->pixel_data[x + y + 1 - w] +
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4 * img_in->pixel_data[x + y + 2 - w] +
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5 * img_in->pixel_data[x + y - 2] +
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12 * img_in->pixel_data[x + y - 1] +
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15 * img_in->pixel_data[x + y] +
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12 * img_in->pixel_data[x + y + 1] +
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5 * img_in->pixel_data[x + y + 2] +
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4 * img_in->pixel_data[x + y - 2 + w] +
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9 * img_in->pixel_data[x + y - 1 + w] +
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12 * img_in->pixel_data[x + y + w] +
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9 * img_in->pixel_data[x + y + 1 + w] +
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4 * img_in->pixel_data[x + y + 2 + w] +
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2 * img_in->pixel_data[x + y - 2 + w + w] +
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4 * img_in->pixel_data[x + y - 1 + w + w] +
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5 * img_in->pixel_data[x + y + w + w] +
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4 * img_in->pixel_data[x + y + 1 + w + w] +
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2 * img_in->pixel_data[x + y + 2 + w + w]) / 159;
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}
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}
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#ifdef CLOCK
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printf("Gaussian noise reduction - time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
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#endif
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}
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/*
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CALC_GRADIENT_SOBEL
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calculates the result of the Sobel operator - http://en.wikipedia.org/wiki/Sobel_operator - and estimates edge direction angle
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*/
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/*void calc_gradient_sobel(struct image * img_in, int g_x[], int g_y[], int g[], int dir[]) {//float theta[]) {*/
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void calc_gradient_sobel(struct image * img_in, int g[], int dir[]) {
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#ifdef CLOCK
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clock_t start = clock();
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#endif
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int w, h, x, y, max_x, max_y, g_x, g_y;
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float g_div;
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w = img_in->width;
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h = img_in->height;
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max_x = w - 3;
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max_y = w * (h - 3);
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for (y = w * 3; y < max_y; y += w) {
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for (x = 3; x < max_x; x++) {
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g_x = (2 * img_in->pixel_data[x + y + 1]
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+ img_in->pixel_data[x + y - w + 1]
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+ img_in->pixel_data[x + y + w + 1]
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- 2 * img_in->pixel_data[x + y - 1]
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- img_in->pixel_data[x + y - w - 1]
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- img_in->pixel_data[x + y + w - 1]);
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g_y = 2 * img_in->pixel_data[x + y - w]
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+ img_in->pixel_data[x + y - w + 1]
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+ img_in->pixel_data[x + y - w - 1]
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- 2 * img_in->pixel_data[x + y + w]
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- img_in->pixel_data[x + y + w + 1]
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- img_in->pixel_data[x + y + w - 1];
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#ifndef ABS_APPROX
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g[x + y] = sqrt(g_x * g_x + g_y * g_y);
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#endif
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#ifdef ABS_APPROX
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g[x + y] = abs(g_x[x + y]) + abs(g_y[x + y]);
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#endif
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if (g_x == 0) {
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dir[x + y] = 2;
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} else {
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g_div = g_y / (float) g_x;
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/* the following commented-out code is slightly faster than the code that follows, but is a slightly worse approximation for determining the edge direction angle
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if (g_div < 0) {
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if (g_div < -1) {
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dir[n] = 0;
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} else {
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dir[n] = 1;
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}
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} else {
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if (g_div > 1) {
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dir[n] = 0;
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} else {
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dir[n] = 3;
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}
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}
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*/
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if (g_div < 0) {
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if (g_div < -2.41421356237) {
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dir[x + y] = 0;
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} else {
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if (g_div < -0.414213562373) {
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dir[x + y] = 1;
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} else {
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dir[x + y] = 2;
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}
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}
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} else {
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if (g_div > 2.41421356237) {
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dir[x + y] = 0;
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} else {
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if (g_div > 0.414213562373) {
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dir[x + y] = 3;
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} else {
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dir[x + y] = 2;
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}
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}
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}
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}
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}
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}
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#ifdef CLOCK
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printf("Calculate gradient Sobel - time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
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#endif
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}
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/*
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CALC_GRADIENT_SCHARR
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calculates the result of the Scharr version of the Sobel operator - http://en.wikipedia.org/wiki/Sobel_operator - and estimates edge direction angle
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may have better rotational symmetry
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*/
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void calc_gradient_scharr(struct image * img_in, int g_x[], int g_y[], int g[], int dir[]) {//float theta[]) {
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#ifdef CLOCK
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clock_t start = clock();
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#endif
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int w, h, x, y, max_x, max_y, n;
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float g_div;
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w = img_in->width;
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h = img_in->height;
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max_x = w - 1;
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max_y = w * (h - 1);
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n = 0;
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for (y = w; y < max_y; y += w) {
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for (x = 1; x < max_x; x++) {
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g_x[n] = (10 * img_in->pixel_data[x + y + 1]
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+ 3 * img_in->pixel_data[x + y - w + 1]
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+ 3 * img_in->pixel_data[x + y + w + 1]
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- 10 * img_in->pixel_data[x + y - 1]
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- 3 * img_in->pixel_data[x + y - w - 1]
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- 3 * img_in->pixel_data[x + y + w - 1]);
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g_y[n] = 10 * img_in->pixel_data[x + y - w]
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+ 3 * img_in->pixel_data[x + y - w + 1]
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+ 3 * img_in->pixel_data[x + y - w - 1]
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- 10 * img_in->pixel_data[x + y + w]
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- 3 * img_in->pixel_data[x + y + w + 1]
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- 3 * img_in->pixel_data[x + y + w - 1];
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#ifndef ABS_APPROX
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g[n] = sqrt(g_x[n] * g_x[n] + g_y[n] * g_y[n]);
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#endif
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#ifdef ABS_APPROX
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g[n] = abs(g_x[n]) + abs(g_y[n]);
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#endif
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if (g_x[n] == 0) {
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dir[n] = 2;
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} else {
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g_div = g_y[n] / (float) g_x[n];
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if (g_div < 0) {
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if (g_div < -2.41421356237) {
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dir[n] = 0;
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} else {
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if (g_div < -0.414213562373) {
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dir[n] = 1;
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} else {
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dir[n] = 2;
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}
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}
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} else {
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if (g_div > 2.41421356237) {
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dir[n] = 0;
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} else {
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if (g_div > 0.414213562373) {
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dir[n] = 3;
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} else {
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dir[n] = 2;
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}
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}
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}
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}
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n++;
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}
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}
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#ifdef CLOCK
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printf("Calculate gradient Scharr - time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
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#endif
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}
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/*
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NON_MAX_SUPPRESSION
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using the estimates of the Gx and Gy image gradients and the edge direction angle determines whether the magnitude of the gradient assumes a local maximum in the gradient direction
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if the rounded edge direction angle is 0 degrees, checks the north and south directions
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if the rounded edge direction angle is 45 degrees, checks the northwest and southeast directions
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if the rounded edge direction angle is 90 degrees, checks the east and west directions
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if the rounded edge direction angle is 135 degrees, checks the northeast and southwest directions
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*/
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void non_max_suppression(struct image * img, int g[], int dir[]) {//float theta[]) {
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#ifdef CLOCK
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clock_t start = clock();
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#endif
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int w, h, x, y, max_x, max_y;
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w = img->width;
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h = img->height;
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max_x = w;
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max_y = w * h;
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for (y = 0; y < max_y; y += w) {
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for (x = 0; x < max_x; x++) {
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switch (dir[x + y]) {
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case 0:
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if(x+y-w-1<0){
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continue;
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}
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if (g[x + y] > g[x + y - w] && g[x + y] > g[x + y + w]) {
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if (g[x + y] > 255) {
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img->pixel_data[x + y] = 0xFF;
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} else {
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img->pixel_data[x + y] = g[x + y];
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}
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} else {
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img->pixel_data[x + y] = 0x00;
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}
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break;
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case 1:
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if(x+y-w-1<0){
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continue;
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}
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if (g[x + y] > g[x + y - w - 1] && g[x + y] > g[x + y + w + 1]) {
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if (g[x + y] > 255) {
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img->pixel_data[x + y] = 0xFF;
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} else {
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img->pixel_data[x + y] = g[x + y];
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}
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} else {
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img->pixel_data[x + y] = 0x00;
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}
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||
|
|
break;
|
||
|
|
case 2:
|
||
|
|
if (g[x + y] > g[x + y - 1] && g[x + y] > g[x + y + 1]) {
|
||
|
|
if (g[x + y] > 255) {
|
||
|
|
img->pixel_data[x + y] = 0xFF;
|
||
|
|
} else {
|
||
|
|
img->pixel_data[x + y] = g[x + y];
|
||
|
|
}
|
||
|
|
} else {
|
||
|
|
img->pixel_data[x + y] = 0x00;
|
||
|
|
}
|
||
|
|
break;
|
||
|
|
case 3:
|
||
|
|
if(x+y-w-1<0){
|
||
|
|
continue;
|
||
|
|
}
|
||
|
|
if (g[x + y] > g[x + y - w + 1] && g[x + y] > g[x + y + w - 1]) {
|
||
|
|
if (g[x + y] > 255) {
|
||
|
|
img->pixel_data[x + y] = 0xFF;
|
||
|
|
} else {
|
||
|
|
img->pixel_data[x + y] = g[x + y];
|
||
|
|
}
|
||
|
|
} else {
|
||
|
|
img->pixel_data[x + y] = 0x00;
|
||
|
|
}
|
||
|
|
break;
|
||
|
|
default:
|
||
|
|
printf("ERROR - direction outside range 0 to 3");
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
#ifdef CLOCK
|
||
|
|
printf("Non-maximum suppression - time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
|
||
|
|
#endif
|
||
|
|
}
|
||
|
|
/*
|
||
|
|
ESTIMATE_THRESHOLD
|
||
|
|
estimates hysteresis threshold, assuming that the top X% (as defined by the HIGH_THRESHOLD_PERCENTAGE) of edge pixels with the greatest intesity are true edges
|
||
|
|
and that the low threshold is equal to the quantity of the high threshold plus the total number of 0s at the low end of the histogram divided by 2
|
||
|
|
*/
|
||
|
|
void estimate_threshold(struct image * img, int * high, int * low) {
|
||
|
|
#ifdef CLOCK
|
||
|
|
clock_t start = clock();
|
||
|
|
#endif
|
||
|
|
int i, max, pixels, high_cutoff;
|
||
|
|
int histogram[256];
|
||
|
|
max = img->width * img->height;
|
||
|
|
for (i = 0; i < 256; i++) {
|
||
|
|
histogram[i] = 0;
|
||
|
|
}
|
||
|
|
for (i = 0; i < max; i++) {
|
||
|
|
histogram[img->pixel_data[i]]++;
|
||
|
|
}
|
||
|
|
pixels = (max - histogram[0]) * HIGH_THRESHOLD_PERCENTAGE;
|
||
|
|
high_cutoff = 0;
|
||
|
|
i = 255;
|
||
|
|
while (high_cutoff < pixels) {
|
||
|
|
high_cutoff += histogram[i];
|
||
|
|
i--;
|
||
|
|
}
|
||
|
|
*high = i;
|
||
|
|
i = 1;
|
||
|
|
while (histogram[i] == 0) {
|
||
|
|
i++;
|
||
|
|
}
|
||
|
|
*low = (*high + i) * LOW_THRESHOLD_PERCENTAGE;
|
||
|
|
#ifdef PRINT_HISTOGRAM
|
||
|
|
for (i = 0; i < 256; i++) {
|
||
|
|
printf("i %d count %d\n", i, histogram[i]);
|
||
|
|
}
|
||
|
|
#endif
|
||
|
|
|
||
|
|
#ifdef CLOCK
|
||
|
|
printf("Estimate threshold - time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
|
||
|
|
#endif
|
||
|
|
}
|
||
|
|
|
||
|
|
void hysteresis (int high, int low, struct image * img_in, struct image * img_out)
|
||
|
|
{
|
||
|
|
#ifdef CLOCK
|
||
|
|
clock_t start = clock();
|
||
|
|
#endif
|
||
|
|
int x, y, n, max;
|
||
|
|
max = img_in->width * img_in->height;
|
||
|
|
for (n = 0; n < max; n++) {
|
||
|
|
img_out->pixel_data[n] = 0x00;
|
||
|
|
}
|
||
|
|
for (y=0; y < img_out->height; y++) {
|
||
|
|
for (x=0; x < img_out->width; x++) {
|
||
|
|
if (img_in->pixel_data[y * img_out->width + x] >= high) {
|
||
|
|
trace (x, y, low, img_in, img_out);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
#ifdef CLOCK
|
||
|
|
printf("Hysteresis - time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
|
||
|
|
#endif
|
||
|
|
}
|
||
|
|
|
||
|
|
int trace(int x, int y, int low, struct image * img_in, struct image * img_out)
|
||
|
|
{
|
||
|
|
int y_off, x_off;//, flag;
|
||
|
|
if (img_out->pixel_data[y * img_out->width + x] == 0)
|
||
|
|
{
|
||
|
|
img_out->pixel_data[y * img_out->width + x] = 0xFF;
|
||
|
|
for (y_off = -1; y_off <=1; y_off++)
|
||
|
|
{
|
||
|
|
for(x_off = -1; x_off <= 1; x_off++)
|
||
|
|
{
|
||
|
|
if (!(y == 0 && x_off == 0) && range(img_in, x + x_off, y + y_off) && img_in->pixel_data[(y + y_off) * img_out->width + x + x_off] >= low) {
|
||
|
|
if (trace(x + x_off, y + y_off, low, img_in, img_out))
|
||
|
|
{
|
||
|
|
return(1);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
return(1);
|
||
|
|
}
|
||
|
|
return(0);
|
||
|
|
}
|
||
|
|
|
||
|
|
int range(struct image * img, int x, int y)
|
||
|
|
{
|
||
|
|
if ((x < 0) || (x >= img->width)) {
|
||
|
|
return(0);
|
||
|
|
}
|
||
|
|
if ((y < 0) || (y >= img->height)) {
|
||
|
|
return(0);
|
||
|
|
}
|
||
|
|
return(1);
|
||
|
|
}
|
||
|
|
|
||
|
|
void dilate_1d_h(struct image * img, struct image * img_out) {
|
||
|
|
int x, y, offset, y_max;
|
||
|
|
y_max = img->height * (img->width - 2);
|
||
|
|
for (y = 2 * img->width; y < y_max; y += img->width) {
|
||
|
|
for (x = 2; x < img->width - 2; x++) {
|
||
|
|
offset = x + y;
|
||
|
|
img_out->pixel_data[offset] = max(max(max(max(img->pixel_data[offset-2], img->pixel_data[offset-1]), img->pixel_data[offset]), img->pixel_data[offset+1]), img->pixel_data[offset+2]);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void dilate_1d_v(struct image * img, struct image * img_out) {
|
||
|
|
int x, y, offset, y_max;
|
||
|
|
y_max = img->height * (img->width - 2);
|
||
|
|
for (y = 2 * img->width; y < y_max; y += img->width) {
|
||
|
|
for (x = 2; x < img->width - 2; x++) {
|
||
|
|
offset = x + y;
|
||
|
|
img_out->pixel_data[offset] = max(max(max(max(img->pixel_data[offset-2 * img->width], img->pixel_data[offset-img->width]), img->pixel_data[offset]), img->pixel_data[offset+img->width]), img->pixel_data[offset+2*img->width]);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void erode_1d_h(struct image * img, struct image * img_out) {
|
||
|
|
int x, y, offset, y_max;
|
||
|
|
y_max = img->height * (img->width - 2);
|
||
|
|
for (y = 2 * img->width; y < y_max; y += img->width) {
|
||
|
|
for (x = 2; x < img->width - 2; x++) {
|
||
|
|
offset = x + y;
|
||
|
|
img_out->pixel_data[offset] = min(min(min(min(img->pixel_data[offset-2], img->pixel_data[offset-1]), img->pixel_data[offset]), img->pixel_data[offset+1]), img->pixel_data[offset+2]);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void erode_1d_v(struct image * img, struct image * img_out) {
|
||
|
|
int x, y, offset, y_max;
|
||
|
|
y_max = img->height * (img->width - 2);
|
||
|
|
for (y = 2 * img->width; y < y_max; y += img->width) {
|
||
|
|
for (x = 2; x < img->width - 2; x++) {
|
||
|
|
offset = x + y;
|
||
|
|
img_out->pixel_data[offset] = min(min(min(min(img->pixel_data[offset-2 * img->width], img->pixel_data[offset-img->width]), img->pixel_data[offset]), img->pixel_data[offset+img->width]), img->pixel_data[offset+2*img->width]);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void erode(struct image * img_in, struct image * img_scratch, struct image * img_out) {
|
||
|
|
#ifdef CLOCK
|
||
|
|
clock_t start = clock();
|
||
|
|
#endif
|
||
|
|
erode_1d_h(img_in, img_scratch);
|
||
|
|
erode_1d_v(img_scratch, img_out);
|
||
|
|
#ifdef CLOCK
|
||
|
|
printf("Erosion - time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
|
||
|
|
#endif
|
||
|
|
}
|
||
|
|
|
||
|
|
void dilate(struct image * img_in, struct image * img_scratch, struct image * img_out) {
|
||
|
|
#ifdef CLOCK
|
||
|
|
clock_t start = clock();
|
||
|
|
#endif
|
||
|
|
dilate_1d_h(img_in, img_scratch);
|
||
|
|
dilate_1d_v(img_scratch, img_out);
|
||
|
|
#ifdef CLOCK
|
||
|
|
printf("Dilation - time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
|
||
|
|
#endif
|
||
|
|
}
|
||
|
|
|
||
|
|
void morph_open(struct image * img_in, struct image * img_scratch, struct image * img_scratch2, struct image * img_out) {
|
||
|
|
#ifdef CLOCK
|
||
|
|
clock_t start = clock();
|
||
|
|
#endif
|
||
|
|
erode(img_in, img_scratch, img_scratch2);
|
||
|
|
dilate(img_scratch2, img_scratch, img_out);
|
||
|
|
#ifdef CLOCK
|
||
|
|
printf("Morphological opening - time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
|
||
|
|
#endif
|
||
|
|
}
|
||
|
|
|
||
|
|
void morph_close(struct image * img_in, struct image * img_scratch, struct image * img_scratch2, struct image * img_out) {
|
||
|
|
#ifdef CLOCK
|
||
|
|
clock_t start = clock();
|
||
|
|
#endif
|
||
|
|
dilate(img_in, img_scratch, img_scratch2);
|
||
|
|
erode(img_scratch2, img_scratch, img_out);
|
||
|
|
#ifdef CLOCK
|
||
|
|
printf("Morphological closing - time elapsed: %f\n", ((double)clock() - start) / CLOCKS_PER_SEC);
|
||
|
|
#endif
|
||
|
|
}
|
||
|
|
|
||
|
|
}
|