OpenCV - 从图像中提取矩形

Question

我试图在此

中提取子图像

二进制阈值，250

轮廓

正如你所看到的，它并不是完美的，它正在拾取一些不是方形的东西。 这是代码：

Mat src; Mat src_gray;
int thresh = 250;
int max_thresh = 255;
RNG rng(12345);

/// Function header
void thresh_callback(int, void*);

 /** @function main */
int main(int argc, char** argv)
{
/// Load source image and convert it to gray
src = imread("Media/RoadSignRecognitionUnknownSigns/RoadSignsComposite1.JPG", 1);

/// Convert image to gray and blur it
cvtColor(src, src_gray, CV_BGR2GRAY);
blur(src_gray, src_gray, Size(3, 3));

/// Create Window
char* source_window = "Source";
namedWindow(source_window, CV_WINDOW_AUTOSIZE);
imshow(source_window, src);

createTrackbar(" Threshold:", "Source", &thresh, max_thresh, thresh_callback);
thresh_callback(0, 0);

waitKey(0);
return(0);
}

/** @function thresh_callback */
void thresh_callback(int, void*)
{
Mat threshold_output;
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;

/// Detect edges using Threshold
threshold(src_gray, threshold_output, thresh, 255, THRESH_BINARY);
imshow("threshold_output", threshold_output);
/// Find contours
findContours(threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE,     Point(0, 0));

/// Approximate contours to polygons + get bounding rects and circles
vector<vector<Point> > contours_poly(contours.size());
vector<Rect> boundRect(contours.size());
vector<Point2f>center(contours.size());
vector<float>radius(contours.size());

for (int i = 0; i < contours.size(); i++)
{
    approxPolyDP(Mat(contours[i]), contours_poly[i], 3, true);
    boundRect[i] = boundingRect(Mat(contours_poly[i]));
    minEnclosingCircle((Mat)contours_poly[i], center[i], radius[i]);
}


/// Draw polygonal contour + bonding rects + circles
Mat drawing = Mat::zeros(threshold_output.size(), CV_8UC3);
for (int i = 0; i< contours.size(); i++)
{
    Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
    drawContours(drawing, contours_poly, i, color, 1, 8, vector<Vec4i>(), 0, Point());
    rectangle(drawing, boundRect[i].tl(), boundRect[i].br(), color, 2, 8, 0);
    circle( drawing, center[i], (int)radius[i], color, 2, 8, 0 );
}

/// Show in a window
namedWindow("Contours", CV_WINDOW_AUTOSIZE);
imshow("Contours", drawing);
for (int i = 0; i < boundRect.size(); i++)
{
    Mat patch = src(boundRect[i]);
    //boundRect[i]
    //Do whatever you want with the patch (imshow, imwrite,...)
    imshow("Patch", patch);
}

for (int i = 0; i < boundRect.size(); i++){
    //int n = 1;// Here you will need to define n differently (for instance pick the largest     contour instead of the first one)
    cv::Rect rect(boundRect[i]);
    cv::Mat miniMat;
    miniMat = src(rect);
    imshow(""+to_string(i), miniMat);
}
}

如何更好地进行形状检测？

Answer 1

如果您的图像与示例中的图像不相交，则可以简单地计算二进制阈值处理中每个连接组件的2d边界框。如果他们几乎不相交，那么你可以先进行侵蚀。

Answer 2

以下是从图像中检测签名的程序：

1. 将图像转换为HSV格式。
2. 从图像HSV中提取红色成分 - H范围（0-10）＆amp;＆amp; （170-180）。
3. 扩张，侵蚀二元红色面具找到边界。
4. 查找轮廓使用RETR_EXTERNAL标志仅提取外轮廓线＆amp;找到该轮廓的边界框。
5. 根据标志牌的已知属性过滤轮廓，例如圆形，三角形，面积，质心，力矩等......
6. 创建一个大小相当于边界框尺寸的标志蒙版图像＆amp;在面具中绘制填充轮廓。
7. 将输入图像的ROI设置为边界框Rect。
8. 提取符号板使用符号掩码图像执行按位和输入。
9. 将图像大小调整为恒定大小可以说100x100＆amp;执行模板匹配/任何其他匹配算法。 另请参阅此示例演示以获取进一步参考。 https://sites.google.com/site/mcvibot2011sep/