OpenCv 2.3 C - 如何隔离图像内的对象

OpenCv 2.3 C - How to isolate object inside image(OpenCv 2.3 C - 如何隔离图像内的对象)

问题描述

我有一个像:

我想删除数字周围的黑色行和列.所以我希望结果是:

i want to remove the black rows and cols round the number. So i want that the result is:

我试试这个:

void findX(IplImage* imgSrc,int* min, int* max){
    int i;
    int minFound=0;
    CvMat data;
    CvScalar maxVal=cvRealScalar(imgSrc->width * 255);
    CvScalar val=cvRealScalar(0);
    //For each col sum, if sum < width*255 then we find the min
    //then continue to end to search the max, if sum< width*255 then is new max
    for (i=0; i< imgSrc->width; i++){
        cvGetCol(imgSrc, &data, i);
        val= cvSum(&data);
        if(val.val[0] < maxVal.val[0]){
            *max= i;
            if(!minFound){
                *min= i;
                minFound= 1;
            }
        }
    }
}

void findY(IplImage* imgSrc,int* min, int* max){
    int i;
    int minFound=0;
    CvMat data;
    CvScalar maxVal=cvRealScalar(imgSrc->width * 255);
    CvScalar val=cvRealScalar(0);
    //For each col sum, if sum < width*255 then we find the min
    //then continue to end to search the max, if sum< width*255 then is new max
    for (i=0; i< imgSrc->height; i++){
        cvGetRow(imgSrc, &data, i);
        val= cvSum(&data);
        if(val.val[0] < maxVal.val[0]){
            *max=i;
            if(!minFound){
                *min= i;
                minFound= 1;
            }
        }
    }
}
CvRect findBB(IplImage* imgSrc){
    CvRect aux;
    int xmin, xmax, ymin, ymax;
    xmin=xmax=ymin=ymax=0;

    findX(imgSrc, &xmin, &xmax);
    findY(imgSrc, &ymin, &ymax);

    aux=cvRect(xmin, ymin, xmax-xmin, ymax-ymin);

    //printf("BB: %d,%d - %d,%d
", aux.x, aux.y, aux.width, aux.height);

    return aux;

}

所以我使用:

IplImage *my_image = cvLoad....
CvRect bb = findBB(my_image);
IplImage *new_image = cvCreateImage(cvSize(bb.width,bb.height), my_image->depth, 1);
cvShowImage("test",new_image);

效果不佳，因为我尝试检查新图像中是否存在黑色行或列.我能做什么?有人能帮我吗?(对不起我的英语！)

it doesn't work good, cause i try to check if in new image there are black rows or cols and they are present. what can i do? can someone help me? (sorry for my english!)

推荐答案

一种方法是简单地执行 边界框技术检测数字，如下图所示:

One way to do it is to simply execute the bounding box technique to detect the digit, as illustrated by the image below:

由于您的图像已经过处理，因此我使用的边界框技术要简单得多.

Since your image is already processed the bounding box technique I use is a lot simpler.

在该过程之后，您真正需要做的就是将原始图像的 ROI(感兴趣区域)设置为框定义的区域，以实现 裁剪 效果并隔离对象:

After that procedure, all you really need to do is set the ROI (Region of Interest) of the original image to the area defined by the box to achieve the crop effect and isolate the object:

请注意，在生成的图像中，边框中有一个额外的非白色行/列像素.好吧，他们也不是黑人.那是因为我没有执行任何阈值方法将图像二值化为黑白.下面的代码演示了在图像的灰度版本上执行的边界框技术.

Notice that in the resulting image there is one extra row/column of pixels in the border that are not white. Well, they are not black either. That's because I didn't performed any threshold method to binarize the image to black and white. The code below demonstrates the bounding box technique being executed on a grayscale version of the image.

这几乎是实现您想要的目标的路线图.出于教育目的，我将分享我使用 OpenCV 的 C++ 接口编写的代码.我相信你有能力将它转换成 C 接口.

This is pretty much the roadmap to achieve what you want. For educational purposes I'm sharing the code I wrote using the C++ interface of OpenCV. I'm sure you are capable of converting it to the C interface.

#include <cv.h>
#include <highgui.h>

#include <vector>


int main(int argc, char* argv[])
{
    cv::Mat img = cv::imread(argv[1]);

    // Convert RGB Mat to GRAY
    cv::Mat gray;
    cv::cvtColor(img, gray, CV_BGR2GRAY);

    // Store the set of points in the image before assembling the bounding box
    std::vector<cv::Point> points;
    cv::Mat_<uchar>::iterator it = gray.begin<uchar>();
    cv::Mat_<uchar>::iterator end = gray.end<uchar>();
    for (; it != end; ++it)
    {
        if (*it) points.push_back(it.pos());
    }

    // Compute minimal bounding box
    cv::RotatedRect box = cv::minAreaRect(cv::Mat(points));

// Draw bounding box in the original image (debug purposes)
//cv::Point2f vertices[4];
//box.points(vertices);
//for (int i = 0; i < 4; ++i)
//{
        //cv::line(img, vertices[i], vertices[(i + 1) % 4], cv::Scalar(0, 255, 0), 1, CV_AA);
/