基于YCrCb颜色空间的CrCb范围筛选法

资料显示，正常黄种人的Cr分量大约在133至173之间，Cb分量大约在77至127之间。可以根据自己的项目需求放大或缩小这两个分量的范围。 void hls::hls_skin_dection(RGB_IMAGE &src, RGB_IMAGE &dst, int rows, int cols, int y_lower, int y_upper, int cb_lower, int cb_upper, int cr_lower, int cr_upper) { for (int row = 0; row < rows; row++) { //#pragma HLS loop_flatten off for (int col = 0; col < cols; col++) { #pragma HLS pipeline II = 1 off RGB_PIXEL src_data; RGB_PIXEL pix; RGB_PIXEL dst_data; bool skin_region; if (row < rows && col < cols) { src >> src_data; } uchar B = src_data.val[0]; uchar G = src_data.val[1]; uchar R = src_data.val[2]; uchar y = (76 * R + 150 * G + 29 * B) >> 8; uchar cb = ((128 * B - 43 * R - 85 * G) >> 8) + 128; uchar cr = ((128 * R - 107 * G - 21 * B) >> 8) + 128; if (y > y_lower && y < y_upper && cb > cb_lower && cb < cb_upper && cr > cr_lower && cr < cr_upper) skin_region = 1; else skin_region = 0; uchar temp0 = (skin_region == 1) ? (uchar)255 : 0; uchar temp1 = (skin_region == 1) ? (uchar)255 : 0; uchar temp2 = (skin_region == 1) ? (uchar)255 : 0; dst_data.val[0] = temp0; dst_data.val[1] = temp1; dst_data.val[2] = temp2; dst << dst_data; } } }

图像边缘检测与重心提取

void hls::hls_edge(RGB_IMAGE &input, RGB_IMAGE &output, int rows, int cols) { RGB_PIXEL lastinPix; double sum_x = 0, sum_y = 0, area = 0; for (int row = 0; row < rows; row++) { lastinPix.val[0] = 0; lastinPix.val[1] = 0; lastinPix.val[2] = 0; for (int col = 0; col < cols; col++) { #pragma HLS pipeline II = 1 off RGB_PIXEL curinPix; RGB_PIXEL outPix; if (row < rows && col < cols) { input >> curinPix; } else { } if (curinPix.val[0] == 255 && curinPix.val[1] == 255 && curinPix.val[2] == 255) { sum_x = sum_x + row; sum_y = sum_y + col; area = area + 1; } if (curinPix.val[0] == 0 && curinPix.val[1] == 0 && curinPix.val[2] == 0 && lastinPix.val[0] == 255 && lastinPix.val[1] == 255 && lastinPix.val[2] == 255) { outPix.val[0] = 255; outPix.val[1] = 255; outPix.val[2] = 255; } else { if (curinPix.val[0] == 255 && curinPix.val[1] == 255 && curinPix.val[2] == 255 && lastinPix.val[0] == 0 && lastinPix.val[1] == 0 && lastinPix.val[2] == 0) { outPix.val[0] = 255; outPix.val[1] = 255; outPix.val[2] = 255; } else { outPix.val[0] = 0; outPix.val[1] = 0; outPix.val[2] = 0; } } lastinPix.val[0] = curinPix.val[0]; lastinPix.val[1] = curinPix.val[1]; lastinPix.val[2] = curinPix.val[2]; output << outPix; } } center.y = round(sum_x / area); center.x = round(sum_y / area); cout << center.x << '\t' << center.y << endl; }