【20160924】GOCVHelper 图像增强部分（3）

//顶帽去光差,radius为模板半径

    Mat moveLightDiff(Mat src,int radius){

        Mat dst;

        Mat srcclone = src.clone();

        Mat mask = Mat::zeros(radius*2,radius*2,CV_8U);

        circle(mask,Point(radius,radius),radius,Scalar(255),-1);

        //顶帽

        erode(srcclone,srcclone,mask);

        dilate(srcclone,srcclone,mask);

        dst =  src - srcclone;

        return dst;

    }

算法来自于冈萨雷斯《数字图像处理教程》形态学篇章。完全按照教程实现，具备一定作用。

 

    //将 DEPTH_8U型二值图像进行细化  经典的Zhang并行快速细化算法

    //细化算法

    void thin(const Mat &src, Mat &dst, const int iterations){

        const int height =src.rows -1;

        const int width  =src.cols -1;

        //拷贝一个数组给另一个数组

        if(src.data != dst.data)

            src.copyTo(dst);

        int n = 0,i = 0,j = 0;

        Mat tmpImg;

        uchar *pU, *pC, *pD;

        bool isFinished =FALSE;

        for(n=0; n<iterations; n++){

            dst.copyTo(tmpImg); 

            isFinished =FALSE;   //一次 先行后列扫描 开始

            //扫描过程一 开始

            for(i=1; i<height;  i++) {

                pU = tmpImg.ptr<uchar>(i-1);

                pC = tmpImg.ptr<uchar>(i);

                pD = tmpImg.ptr<uchar>(i+1);

                for(int j=1; j<width; j++){

                    if(pC[j] > 0){

                        int ap=0;

                        int p2 = (pU[j] >0);

                        int p3 = (pU[j+1] >0);

                        if (p2==0 && p3==1)

                            ap++;

                        int p4 = (pC[j+1] >0);

                        if(p3==0 && p4==1)

                            ap++;

                        int p5 = (pD[j+1] >0);

                        if(p4==0 && p5==1)

                            ap++;

                        int p6 = (pD[j] >0);

                        if(p5==0 && p6==1)

                            ap++;

                        int p7 = (pD[j-1] >0);

                        if(p6==0 && p7==1)

                            ap++;

                        int p8 = (pC[j-1] >0);

                        if(p7==0 && p8==1)

                            ap++;

                        int p9 = (pU[j-1] >0);

                        if(p8==0 && p9==1)

                            ap++;

                        if(p9==0 && p2==1)

                            ap++;

                        if((p2+p3+p4+p5+p6+p7+p8+p9)>1 && (p2+p3+p4+p5+p6+p7+p8+p9)<7){

                            if(ap==1){

                                if((p2*p4*p6==0)&&(p4*p6*p8==0)){                           

                                    dst.ptr<uchar>(i)[j]=0;

                                    isFinished =TRUE;                            

                                }

                            }

                        }                    

                    }

 

                } //扫描过程一 结束

                dst.copyTo(tmpImg); 

                //扫描过程二 开始

                for(i=1; i<height;  i++){

                    pU = tmpImg.ptr<uchar>(i-1);

                    pC = tmpImg.ptr<uchar>(i);

                    pD = tmpImg.ptr<uchar>(i+1);

                    for(int j=1; j<width; j++){

                        if(pC[j] > 0){

                            int ap=0;

                            int p2 = (pU[j] >0);

                            int p3 = (pU[j+1] >0);

                            if (p2==0 && p3==1)

                                ap++;

                            int p4 = (pC[j+1] >0);

                            if(p3==0 && p4==1)

                                ap++;

                            int p5 = (pD[j+1] >0);

                            if(p4==0 && p5==1)

                                ap++;

                            int p6 = (pD[j] >0);

                            if(p5==0 && p6==1)

                                ap++;

                            int p7 = (pD[j-1] >0);

                            if(p6==0 && p7==1)

                                ap++;

                            int p8 = (pC[j-1] >0);

                            if(p7==0 && p8==1)

                                ap++;

                            int p9 = (pU[j-1] >0);

                            if(p8==0 && p9==1)

                                ap++;

                            if(p9==0 && p2==1)

                                ap++;

                            if((p2+p3+p4+p5+p6+p7+p8+p9)>1 && (p2+p3+p4+p5+p6+p7+p8+p9)<7){

                                if(ap==1){

                                    if((p2*p4*p8==0)&&(p2*p6*p8==0)){                           

                                        dst.ptr<uchar>(i)[j]=0;

                                        isFinished =TRUE;                            

                                    }

                                }

                            }                    

                        }

                    }

                } //一次 先行后列扫描完成          

                //如果在扫描过程中没有删除点，则提前退出

                if(isFinished ==FALSE)

                    break; 

            }

        }

    }

#end of thin

细化算法，在处理毛笔字一类的时候效果很好。使用的过程中，注意需要保留的部分要处理为白色，也就是scalar(255)

 

来自为知笔记(Wiz)