有赞零售小票打印图片二值化方案

/** 获取灰度图
 @param bit_map 图像像素数组地址（ ARGB 格式） @param width 图像宽 @param height 图像高 @return 灰度图像素数组地址 */int * gray_image(int *bit_map, int width, int height) {  double pixel_total = width * height; // 像素总数  if (pixel_total == 0) return NULL;  // 灰度像素点存储  int *gray_pixels = (int *)malloc(pixel_total * sizeof(int));  memset(gray_pixels, 0, pixel_total * sizeof(int));  int *p = bit_map;  for (u_int i = 0; i < pixel_total; i++, p++) {    // 分离三原色及透明度    u_char alpha = ((*p & 0xFF000000) >> 24);    u_char red = ((*p & 0xFF0000) >> 16);    u_char green = ((*p & 0x00FF00) >> 8);    u_char blue = (*p & 0x0000FF);
    u_char gray = (red*38 + green*75 + blue*15) >> 7;    if (alpha == 0 && gray == 0) {      gray = 0xFF;    }    gray_pixels[i] = gray;  }  return gray_pixels;}

ω0 = N0 / M × N                            (1)ω1 = N1 / M × N                            (2)N0 + N1 = M × N                             (3)ω0 + ω1 = 1                                (4)μ = ω0 * μ0 + ω1 * μ1                   (5)g = ω0 * (μ0 - μ)^2 + ω1 * (μ1 - μ)^2  (6)

g = ω0 * ω1 * (μ0 - μ1)^2                (7)

/** OTSU 算法获取二值图
 @param bit_map 图像像素数组地址（ ARGB 格式） @param width 图像宽 @param height 图像高 @param T 存储计算得出的阈值 @return 二值图像素数组地址 */int * binary_image_with_otsu_threshold_alg(int *bit_map, int width, int height, int *T) {
  double pixel_total = width * height; // 像素总数  if (pixel_total == 0) return NULL;
  unsigned long sum1 = 0; // 总灰度值  unsigned long sumB = 0; // 背景总灰度值  double wB = 0.0;    // 背景像素点比例  double wF = 0.0;    // 前景像素点比例  double mB = 0.0;    // 背景平均灰度值  double mF = 0.0;    // 前景平均灰度值  double max_g = 0.0;   // 最大类间方差  double g = 0.0;     // 类间方差  u_char threshold = 0;  // 阈值  double histogram[256] = {0}; // 灰度直方图，下标是灰度值，保存内容是灰度值对应的像素点总数
  // 获取灰度直方图和总灰度  int *gray_pixels = (int *)malloc(pixel_total * sizeof(int));  memset(gray_pixels, 0, pixel_total * sizeof(int));  int *p = bit_map;  for (u_int i = 0; i < pixel_total; i++, p++) {    // 分离三原色及透明度    u_char alpha = ((*p & 0xFF000000) >> 24);    u_char red = ((*p & 0xFF0000) >> 16);    u_char green = ((*p & 0x00FF00) >> 8);    u_char blue = (*p & 0x0000FF);
    u_char gray = (red*38 + green*75 + blue*15) >> 7;    if (alpha == 0 && gray == 0) {      gray = 0xFF;    }    gray_pixels[i] = gray;
    // 计算灰度直方图分布，Histogram 数组下标是灰度值，保存内容是灰度值对应像素点数    histogram[gray]++;    sum1 += gray;  }
  // OTSU 算法  for (u_int i = 0; i < 256; i++)  {    wB = wB + histogram[i]; // 这里不算比例，减少运算，不会影响求 T    wF = pixel_total - wB;    if (wB == 0 || wF == 0)    {      continue;    }    sumB = sumB + i * histogram[i];    mB = sumB / wB;    mF = (sum1 - sumB) / wF;    g = wB * wF * (mB - mF) * (mB - mF);    if (g >= max_g)    {      threshold = i;      max_g = g;    }  }
  for (u_int i = 0; i < pixel_total; i++) {    gray_pixels[i] = gray_pixels[i] <= threshold ? 0xFF000000:0xFFFFFFFF;  }
  if (T) {    *T = threshold;  // OTSU 算法阈值  }
  return gray_pixels;}

/** 平均灰度算法获取二值图
 @param bit_map 图像像素数组地址（ ARGB 格式） @param width 图像宽 @param height 图像高 @param T 存储计算得出的阈值 @return 二值图像素数组地址 */int * binary_image_with_average_gray_threshold_alg(int *bit_map, int width, int height, int *T) {
  double pixel_total = width * height; // 像素总数  if (pixel_total == 0) return NULL;
  unsigned long sum = 0; // 总灰度  u_char threshold = 0;  // 阈值

  int *gray_pixels = (int *)malloc(pixel_total * sizeof(int));  memset(gray_pixels, 0, pixel_total * sizeof(int));  int *p = bit_map;  for (u_int i = 0; i < pixel_total; i++, p++) {    // 分离三原色及透明度    u_char alpha = ((*p & 0xFF000000) >> 24);    u_char red = ((*p & 0xFF0000) >> 16);    u_char green = ((*p & 0x00FF00) >> 8);    u_char blue = (*p & 0x0000FF);
    u_char gray = (red*38 + green*75 + blue*15) >> 7;    if (alpha == 0 && gray == 0) {      gray = 0xFF;    }    gray_pixels[i] = gray;    sum += gray;  }  // 计算平均灰度  threshold = sum / pixel_total;
  for (u_int i = 0; i < pixel_total; i++) {    gray_pixels[i] = gray_pixels[i] <= threshold ? 0xFF000000:0xFFFFFFFF;  }
  if (T) {    *T = threshold;  }
  return gray_pixels;}

// 判断是否是双峰直方图int is_double_peak(double *histogram) {  // 判断直方图是存在双峰  int peak_count = 0;  for (int i = 1; i < 255; i++) {    if (histogram[i - 1] < histogram[i] && histogram[i + 1] < histogram[i]) {      peak_count++;      if (peak_count > 2) return 0;    }  }  return peak_count == 2;}
/** 双峰平均值算法获取二值图
 @param bit_map 图像像素数组地址（ ARGB 格式） @param width 图像宽 @param height 图像高 @param T 存储计算得出的阈值 @return 二值图像素数组地址 */int * binary_image_with_average_peak_threshold_alg(int *bit_map, int width, int height, int *T) {  double pixel_total = width * height; // 像素总数  if (pixel_total == 0) return NULL;
  // 灰度直方图，下标是灰度值，保存内容是灰度值对应的像素点总数  double histogram1[256] = {0};  double histogram2[256] = {0}; // 求均值的过程会破坏前面的数据，因此需要两份数据  u_char threshold = 0;  // 阈值
  // 获取灰度直方图  int *gray_pixels = (int *)malloc(pixel_total * sizeof(int));  memset(gray_pixels, 0, pixel_total * sizeof(int));  int *p = bit_map;  for (u_int i = 0; i < pixel_total; i++, p++) {    // 分离三原色及透明度    u_char alpha = ((*p & 0xFF000000) >> 24);    u_char red = ((*p & 0xFF0000) >> 16);    u_char green = ((*p & 0x00FF00) >> 8);    u_char blue = (*p & 0x0000FF);
    u_char gray = (red*38 + green*75 + blue*15) >> 7;    if (alpha == 0 && gray == 0) {      gray = 0xFF;    }    gray_pixels[i] = gray;
    // 计算灰度直方图分布，Histogram数组下标是灰度值，保存内容是灰度值对应像素点数    histogram1[gray]++;    histogram2[gray]++;  }
  // 如果不是双峰，则通过三点求均值来平滑直方图  int times = 0;  while (!is_double_peak(histogram2)) {    times++;    if (times > 1000) {        // 这里使用 1000 次，考虑到过多次循环可能会存在性能问题      return NULL;             // 似乎直方图无法平滑为双峰的，返回错误代码    }    histogram2[0] = (histogram1[0] + histogram1[0] + histogram1[1]) / 3;          // 第一点    for (int i = 1; i < 255; i++) {      histogram2[i] = (histogram1[i - 1] + histogram1[i] + histogram1[i + 1]) / 3;    // 中间的点    }    histogram2[255] = (histogram1[254] + histogram1[255] + histogram1[255]) / 3;      // 最后一点    memcpy(histogram1, histogram2, 256 * sizeof(double));                 // 备份数据，为下一次迭代做准备  }
  // 求阈值T  int peak[2] = {0};  for (int i = 1, y = 0; i < 255; i++) {    if (histogram2[i - 1] < histogram2[i] && histogram2[i + 1] < histogram2[i]) {      peak[y++] = i;    }  }  threshold = (peak[0] + peak[1]) / 2;
  for (u_int i = 0; i < pixel_total; i++) {    gray_pixels[i] = gray_pixels[i] <= threshold ? 0xFF000000:0xFFFFFFFF;  }
  if (T) {    *T = threshold;  }
  return gray_pixels;}