OpenCV边缘提取

边缘检测是图像处理中的一种传统算法，可以用来做物体检测。偶然间看到一个例子，形态学操作实为巧妙，稍作分析记录下来，同时分享给像我一样的小白。代码经过整理如下：

#include<iostream>
#define max(a,b) a>b?a:b
using namespace std;
int main()
｛
	cv::Mat pupil_image = cv::imread("test.jpg",0);
	cv::Mat binary_img, spec_mask, kernel;
	cv::Mat histogram;
	int histSize;
	histSize = 256;	
	float range[] = { 0, 256 }; 
	const float* histRange = { range };
	int max_intensity = 40, lowest_spike_index = 255, highest_spike_index =0;
	cv::calcHist(&pupil_image, 1, 0, cv::Mat(), histogram, 1, &histSize, &histRange, true, false);
	for (int i = 0; i < histogram.rows; i++) {
		const float intensity = histogram.at<float>(i, 0);
		if (intensity > 40) {
			max_intensity = max(intensity, max_intensity);
			lowest_spike_index = min(lowest_spike_index, i);
			highest_spike_index = max(highest_spike_index, i);
		}
	}
	cv::inRange(pupil_image, cv::Scalar(0), cv::Scalar(lowest_spike_index + 20), binary_img);