DSP

DSP移植-全局阈值分割

2019-07-13 10:56发布

站内文章 / DSP
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 由于阈值处理直观、实现简单且计算速度快，而且EMCV中不含有该算法，下面用OpenCV给出实现的代码。 1.  处理流程：
1）.为全局阈值选择一个初始估计值T(图像的平均灰度)。 2）.用T分割图像。产生两组像素：G1有灰度值大于T的像素组成，G2有小于等于T像素组成。 3）.计算G1和G2像素的平均灰度值m1和m2； 4）.计算一个新的阈值:T = (m1 + m2) / 2; 5）.重复步骤2和4,直到连续迭代中的T值间的差为零。
2.源代码： //gray image U8 全局阈值分割 int vicIsodataThreshold(IplImage *p_image_in, float offset, int *threshold) { int ret = 0; int i, j; int T = 0; unsigned char *data; unsigned char *data_line; if (NULL == p_image_in || NULL == threshold) { return -1; } float T0 = 0.0;//初始阈值 float sum_0 = 0.0; for (i = 0 ; i< p_image_in->height ; i++) { data = (unsigned char *)p_image_in->imageData + i * p_image_in->widthStep; for (j =0 ; j < p_image_in->width;j++) { data_line = data + j; sum_0 += (float)*data_line; } } T0 = sum_0 / (p_image_in->height * p_image_in->width); T = (int)(T0 + 0.5); float T1 = 0.0, T2 = 0.0; float sum_1 = 0.0, sum_2 = 0.0; int count1, count2; float dT = 255.0; //计算T两侧的灰度平均值，然后把二者的均值赋值给T while (dT > offset) { T1 = 0.0; T2 = 0.0; sum_1 = 0.0; sum_2 = 0.0; count1 = 0; count2 = 0; for (i = 0 ; i< p_image_in->height ; i++) { data = (unsigned char *)p_image_in->imageData + i * p_image_in->widthStep; for (j =0 ; j < p_image_in->width;j++) { data_line = data + j; if (*data_line >= T) { sum_1 += (float)*data_line;; count1++; } else if(*data_line < T) { sum_2 += (float)*data_line;; count2++; } } } T1 = sum_1 / count1; T2 = sum_2 / count2; dT = fabs(T - (T1 + T2)/2); T = (T1 + T2)/2; cout<<"the T is "<

reference：http://blog.csdn.net/renshengrumenglibing/article/details/7251127

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