我正在使用
android openCV,我想检测图像中的三角形,矩形和圆形.所以我这样做:Canny => findContours => approxpolyDP并获取此图片:
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Image Hosted by ImageShack.us http://imageshack.us/a/img839/8100/device20130114224716.png
但是,approxpolyDP的结果包含很多顶点,所以我无法确定它是哪个形状.为了消除顶点,我想检测每个轮廓中的线并找到它们的交点.如何为单个轮廓做到这一点?
解决方法
对于圆圈检测,请使用
HoughCircles.
然后在这里你只是寻找简化的多边形(三角形和正方形).你试过在aptpolyDP中调整epsilon吗?
以下是openCV squares.cpp sample code的示例代码段 – 了解近似精度(epsilon,aboutpolyDP的第三个参数)是如何相对于轮廓的大小设置的.
C代码,但openCV接口应该是相同的,所以我确信它可以直接适应您的环境.
// test each contour for( size_t i = 0; i < contours.size(); i++ ) { // approximate contour with accuracy proportional // to the contour perimeter approxpolyDP(Mat(contours[i]),approx,arcLength(Mat(contours[i]),true)*0.02,true); // square contours should have 4 vertices after approximation // relatively large area (to filter out noisy contours) // and be convex. // Note: absolute value of an area is used because // area may be positive or negative - in accordance with the // contour orientation if( approx.size() == 4 && fabs(contourArea(Mat(approx))) > 1000 && isContourConvex(Mat(approx)) ) { double maxCosine = 0; for( int j = 2; j < 5; j++ ) { // find the maximum cosine of the angle between joint edges double cosine = fabs(angle(approx[j%4],approx[j-2],approx[j-1])); maxCosine = MAX(maxCosine,cosine); } // if cosines of all angles are small // (all angles are ~90 degree) then write quandrange // vertices to resultant sequence if( maxCosine < 0.3 ) squares.push_back(approx); } }