利用种子填充法对二值图像进行连通域标记

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利用种子填充法对二值图像进行连通域标记

最近一直在用OpenCV做设计,其中有一个设计环节是设计检测二值图像的连通域及其特征,在网上搜了一下算法,看到了有two-pass法和种子填充法两种。两种经典的方法都编程实现过,个人觉得,种子填充法比较直观,不需要像two-pass法那么绕,只需要遍历一遍图像,而且还能顺带计算面积和外接矩形框,

种子填充法原理

关于种子填充法的详细原理可以参考OpenCV_连通区域分析(Connected Component Analysis/Labeling)

大致算法如下:
设二值化图像A中,像素值为255的点是前景,为0的点是背景。A(x, y)为坐标(x, y)处的像素值,遍历图像的每个像素:
1、 如果像素值不等于255,则继续访问下一个元素。
2、 如果像素值为A(x, y) = 255,则新建一个新的label,当前值A(x, y) = label,并且
a. 检查其4个邻域,如果有属于前景的像素也给它赋予label值,并将它的坐标压栈。
b. 弹出栈顶坐标,重复a的过程,知道堆栈为空。
此时,便找到了一个连通区域,该区域内的像素值被标记为label。

3、 重复1、2的过程,检测出所有的区域。

动态演示

废话少说,上代码!

实现程序

该程序基于OpenCV2.4.9 和VS2010平台:

#include <opencv2\opencv.hpp>#include <iostream>#include <vector>#include <stack>using namespace std;using namespace cv;typedef struct _Feather{    int label;              // 连通域的label值    int area;               // 连通域的面积    Rect boundingbox;       // 连通域的外接矩形框} Feather;/* Input:     src: 待检测连通域的二值化图像Output:    dst: 标记后的图像    featherList: 连通域特征的清单return:     连通域数量。*/int bwLabel(Mat & src, Mat & dst, vector<Feather> & featherList){    int rows = src.rows;    int cols = src.cols;    int labelValue = 0;    Point seed, neighbor;    stack<Point> pointStack;    // 堆栈    int area = 0;               // 用于计算连通域的面积    int leftBoundary = 0;       // 连通域的左边界,即外接最小矩形的左边框,横坐标值,依此类推    int rightBoundary = 0;    int topBoundary = 0;    int bottomBoundary = 0;    Rect box;                   // 外接矩形框    Feather feather;    featherList.clear();    // 清除数组    dst.release();    dst = src.clone();    for( int i = 0; i < rows; i++)    {        uchar *pRow = dst.ptr<uchar>(i);        for( int j = 0; j < cols; j++)        {            if(pRow[j] == 255)            {                area = 0;                labelValue++;           // labelValue最大为254,最小为1.                seed = Point(j, i);     // Point(横坐标,纵坐标)                dst.at<uchar>(seed) = labelValue;                pointStack.push(seed);                area++;                leftBoundary = seed.x;                rightBoundary = seed.x;                topBoundary = seed.y;                bottomBoundary = seed.y;                while(!pointStack.empty())                {                    neighbor = Point(seed.x+1, seed.y);                    if((seed.x != (cols-1)) && (dst.at<uchar>(neighbor) == 255))                    {                        dst.at<uchar>(neighbor) = labelValue;                        pointStack.push(neighbor);                        area++;                        if(rightBoundary < neighbor.x)                            rightBoundary = neighbor.x;                    }                    neighbor = Point(seed.x, seed.y+1);                    if((seed.y != (rows-1)) && (dst.at<uchar>(neighbor) == 255))                    {                        dst.at<uchar>(neighbor) = labelValue;                        pointStack.push(neighbor);                        area++;                        if(bottomBoundary < neighbor.y)                            bottomBoundary = neighbor.y;                    }                    neighbor = Point(seed.x-1, seed.y);                    if((seed.x != 0) && (dst.at<uchar>(neighbor) == 255))                    {                        dst.at<uchar>(neighbor) = labelValue;                        pointStack.push(neighbor);                        area++;                        if(leftBoundary > neighbor.x)                            leftBoundary = neighbor.x;                    }                    neighbor = Point(seed.x, seed.y-1);                    if((seed.y != 0) && (dst.at<uchar>(neighbor) == 255))                    {                        dst.at<uchar>(neighbor) = labelValue;                        pointStack.push(neighbor);                        area++;                        if(topBoundary > neighbor.y)                            topBoundary = neighbor.y;                    }                    seed = pointStack.top();                    pointStack.pop();                }                box = Rect(leftBoundary, topBoundary, rightBoundary-leftBoundary, bottomBoundary-topBoundary);                rectangle(src, box, 255);                feather.area = area;                feather.boundingbox = box;                feather.label = labelValue;                featherList.push_back(feather);            }        }    }    return labelValue;}int main(int argc, char *argv[]){    Mat src(imread("shape.jpg", 0));    if(src.empty())        exit(-1);    threshold(src, src, 127, 255, THRESH_BINARY);   // 二值化图像    vector<Feather> featherList;                    // 存放连通域特征    Mat dst;    cout << "连通域数量: " << bwLabel(src, dst, featherList) << endl;    // 为了方便观察,可以将label“放大”    for( int i = 0; i < dst.rows; i++)    {        uchar *p = dst.ptr<uchar>(i);        for( int j = 0; j < dst.cols; j++)        {            p[j] = 30*p[j];        }    }    cout << "标号" << "\t" << "面积" << endl;    for(vector<Feather>::iterator it = featherList.begin(); it < featherList.end(); it++)    {        cout << it->label << "\t" << it->area << endl;        rectangle(dst, it->boundingbox, 255);    }    imshow("src", src);    imshow("dst", dst);    waitKey();    destroyAllWindows();    system("pause");    return 0;}

运行结果:

原图:
运行结果:src

检测结果:
这里写图片描述

特征清单:
这里写图片描述

请多多指教!

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