在Opencv中实现Matlab的bwareaopen函数功能

在Matlab中，我们通常利用bwareaopen函数去除八邻域内面积小于一定值的连通域。
matlab函数bwareaopen──删除小面积对象
格式：BW2 = bwareaopen(BW,P,conn)
作用：删除二值图像BW中面积小于P的对象，默认情况下使用8邻域。

Opencv里没有特定的函数实现该功能，但我们可以自己设计一个孔洞填充/小区域去除的方式来实现。
函数接口设计如下：
C++
void RemoveSmallRegion(Mat& Src, Mat& Dst, int AreaLimit, int CheckMode, int NeihborMode)

其中，Src为源图像，Dst为目标图像，AreaLimit为连通域的面积，CheckMode为模式选择，其中0为去除小面积区域，1为孔洞填充。NeihborMode为邻域类型，可以为4邻域或者8邻域。
下面是实现的代码。

#include <cv.h>
#include <highgui.h>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
#include <vector>    

using namespace cv;
using namespace std;  

void RemoveSmallRegion(Mat& Src, Mat& Dst, int AreaLimit=50, int CheckMode=1, int NeihborMode=0);  

int main()
{
    double t = (double)getTickCount();  

    char* imagePath = "E:\SVM\局部.jpg";
    char* OutPath = "E:\SVM\局部_去除孔洞.jpg";  

    Mat Src = imread(imagePath, CV_LOAD_IMAGE_GRAYSCALE);
    Mat Dst = Mat::zeros(Src.size(), CV_8UC1);  

    //二值化处理
    for(int i = 0; i < Src.rows; ++i)
    {
        uchar* iData = Src.ptr<uchar>(i);
        for(int j = 0; j < Src.cols; ++j)
        {
            if(iData[j] == 0 || iData[j]==255) continue;
            else if (iData[j] < 10)
            {
                iData[j] = 0;
                //cout<<'#';
            }
            else if (iData[j] > 10)
            {
                iData[j] = 255;
                //cout<<'!';
            }
        }
    }
    cout<<"Image Binary processed."<<endl;  

    RemoveSmallRegion(Src, Dst, 20, 1, 1);
    RemoveSmallRegion(Dst, Dst, 20, 0, 0);
    cout<<"Done!"<<endl;
    imwrite(OutPath, Dst);  

    t = ((double)getTickCount() - t)/getTickFrequency();
    cout<<"Time cost: "<<t<<" sec."<<endl;  

    return 0;
}    

//CheckMode: 0代表去除黑区域，1代表去除白区域; NeihborMode：0代表4邻域，1代表8邻域;
void RemoveSmallRegion(Mat& Src, Mat& Dst, int AreaLimit, int CheckMode, int NeihborMode)
{
    int RemoveCount=0;       //记录除去的个数
    //记录每个像素点检验状态的标签，0代表未检查，1代表正在检查,2代表检查不合格（需要反转颜色），3代表检查合格或不需检查
    Mat Pointlabel = Mat::zeros( Src.size(), CV_8UC1 );  

    if(CheckMode==1)
    {
        cout<<"Mode: 去除小区域. ";
        for(int i = 0; i < Src.rows; ++i)
        {
            uchar* iData = Src.ptr<uchar>(i);
            uchar* iLabel = Pointlabel.ptr<uchar>(i);
            for(int j = 0; j < Src.cols; ++j)
            {
                if (iData[j] < 10)
                {
                    iLabel[j] = 3;
                }
            }
        }
    }
    else
    {
        cout<<"Mode: 去除孔洞. ";
        for(int i = 0; i < Src.rows; ++i)
        {
            uchar* iData = Src.ptr<uchar>(i);
            uchar* iLabel = Pointlabel.ptr<uchar>(i);
            for(int j = 0; j < Src.cols; ++j)
            {
                if (iData[j] > 10)
                {
                    iLabel[j] = 3;
                }
            }
        }
    }  

    vector<Point2i> NeihborPos;  //记录邻域点位置
    NeihborPos.push_back(Point2i(-1, 0));
    NeihborPos.push_back(Point2i(1, 0));
    NeihborPos.push_back(Point2i(0, -1));
    NeihborPos.push_back(Point2i(0, 1));
    if (NeihborMode==1)
    {
        cout<<"Neighbor mode: 8邻域."<<endl;
        NeihborPos.push_back(Point2i(-1, -1));
        NeihborPos.push_back(Point2i(-1, 1));
        NeihborPos.push_back(Point2i(1, -1));
        NeihborPos.push_back(Point2i(1, 1));
    }
    else cout<<"Neighbor mode: 4邻域."<<endl;
    int NeihborCount=4+4*NeihborMode;
    int CurrX=0, CurrY=0;
    //开始检测
    for(int i = 0; i < Src.rows; ++i)
    {
        uchar* iLabel = Pointlabel.ptr<uchar>(i);
        for(int j = 0; j < Src.cols; ++j)
        {
            if (iLabel[j] == 0)
            {
                //********开始该点处的检查**********
                vector<Point2i> GrowBuffer;                                      //堆栈，用于存储生长点
                GrowBuffer.push_back( Point2i(j, i) );
                Pointlabel.at<uchar>(i, j)=1;
                int CheckResult=0;                                               //用于判断结果（是否超出大小），0为未超出，1为超出  

                for ( int z=0; z<GrowBuffer.size(); z++ )
                {  

                    for (int q=0; q<NeihborCount; q++)                                      //检查四个邻域点
                    {
                        CurrX=GrowBuffer.at(z).x+NeihborPos.at(q).x;
                        CurrY=GrowBuffer.at(z).y+NeihborPos.at(q).y;
                        if (CurrX>=0&&CurrX<Src.cols&&CurrY>=0&&CurrY<Src.rows)  //防止越界
                        {
                            if ( Pointlabel.at<uchar>(CurrY, CurrX)==0 )
                            {
                                GrowBuffer.push_back( Point2i(CurrX, CurrY) );  //邻域点加入buffer
                                Pointlabel.at<uchar>(CurrY, CurrX)=1;           //更新邻域点的检查标签，避免重复检查
                            }
                        }
                    }  

                }
                if (GrowBuffer.size()>AreaLimit) CheckResult=2;                 //判断结果（是否超出限定的大小），1为未超出，2为超出
                else {CheckResult=1;   RemoveCount++;}
                for (int z=0; z<GrowBuffer.size(); z++)                         //更新Label记录
                {
                    CurrX=GrowBuffer.at(z).x;
                    CurrY=GrowBuffer.at(z).y;
                    Pointlabel.at<uchar>(CurrY, CurrX) += CheckResult;
                }
                //********结束该点处的检查**********  

            }
        }
    }    

    CheckMode=255*(1-CheckMode);
    //开始反转面积过小的区域
    for(int i = 0; i < Src.rows; ++i)
    {
        uchar* iData = Src.ptr<uchar>(i);
        uchar* iDstData = Dst.ptr<uchar>(i);
        uchar* iLabel = Pointlabel.ptr<uchar>(i);
        for(int j = 0; j < Src.cols; ++j)
        {
            if (iLabel[j] == 2)
            {
                iDstData[j] = CheckMode;
            }
            else if(iLabel[j] == 3)
            {
                iDstData[j] = iData[j];
            }
        }
    }   

    cout<<RemoveCount<<" objects removed."<<endl;
}  

原文:大专栏  在Opencv中实现Matlab的bwareaopen函数功能

原文地址：https://www.cnblogs.com/dajunjun/p/11651546.html