opencv rectangle detection

In the. \ opencv \ doc \ vidsurv folder, there are three doc FILES: blob_tracking_modules, blob_tracking_tests, and testseq. Among them, blob_tracking_modules must be read in detail. "FG/BG Detection"Module into msforeground/background segmentation for each pixel. "Blob entering Detection"Module uses theresult (fg/BG mask) of" fg/BG

Image algorithm Test IteratoralgorithmfeaturesOriginal articles, reproduced please specify the source: http://blog.csdn.net/crzy_sparrow/article/details/7391511Article directory:First, Harris Angle point detection basic theorySecond, OPENCV code implementationThird, improved Harris corner point detectionFour, fast corner point detectionV. ReferencesVi. Appendices (information and source code)First, Harris C

First of all, has been considering such a great opencv should change some of the outdated things, such as: detectors, recognizers and so on, sure enough, openv the big guys or secretly changed. Direct load Caffe Depth learning (SSD face detection) model has been OPENCV: (a powerful one) Here's the Python code: Use Picture: Python detect_faces.py--image rooster.jp

In the previous article, "OpenCV feature2d learning--surf and SIFT operators to achieve feature point detection", the use of SIFT and surf operators for feature point detection, here is trying to use fast operator for feature point detection.Fast's full name is:Features from Accelerated Segment test, the main feature values are fast, much faster than other known

"OpenCV Getting Started" chapter III Canny edge detection The image edge detection principle is to detect the image of all the gray value changes in the larger point, and these points are connected to form a number of lines, these lines can be called the edge of the image. The canny edge detection operator is a multi-

I haven't written a blog for a long time, and my student's career ends. I will not summarize it. Today, I will record the Adaboost training and detection process in opencv, so that it is convenient for others ~~~ Ah, haha ~~~~ I. Basic Knowledge preparation First, opencv currently only supports training and detection

#include"stdafx.h"#defineMax_corners 20intMain () {intCornernum =max_corners; VectorCorner; DoubleQualitylevel =0.05; DoubleMindistance =5; Doublescalar =0.5; Mat SRCIMG,SRCIMG1; Mat Grayimg,grayimg1,grayimg2; Mat disimg; inti; //videocapture Video ("e:\\c_vc_code\\text_photo\\feini.flv");Videocapture Video (0); if(!video.isopened ()) { return-1; } Video>>srcimg; Resize (srcimg,srcimg1,size (Srcimg.cols*scalar,srcimg.rows*scalar),1,1,3); Cvtcolor (Srcimg1,grayimg,cv_bgr2gray,1);

Hough Line transformation can only be the edge binary image.4. The specific principles of the Hough Line detection refer to:52944708Http://www.opencv.org.cn/opencvdoc/2.3.2/html/doc/tutorials/imgproc/imgtrans/hough_lines/hough_lines.htmlhttp://lib.csdn.net/article/opencv/24201The code is as follows:#Line Detection#using Hough linear transformation to do straight

Recently began to learn OPENCV, want to detect the ring on the picture, found that Hough transform can do such an effect, so try to use the Opencv3 Hough transform to do the next ring detection. OpenCV in the Hough transform function: The first parameter, the Inputarray type of image, is the 8-bit grayscale single-channel image, which is the source image.The se

write in front of the articleThese days because the work needs to learn image detection, stupid I do not want to stare at OPENCV start to learn (; ′⌒ '), even the ability to check information is weak 〒▽〒Praise My best man ticket (*^▽^*) The man is not the image processing but love my stupid (the "contest")Let me give him the request (our store?? Omega??) Our store??? He put the game down and spent a day or

OPENCV provides two programs that can train their own cascading classifiers opencv_haartraining and Opencv_traincascade. Opencv_traincascade is a new program that is written in C + + using the OpenCV 2.x API. The main difference is that Opencv_traincascade supports both Haar and LBP (local Binary Patterns), and it is easy to add other features. Compared with the Haar feature, LBP features are integer featur

The realization of vehicle detection and tracking based on OpenCV Http://www.cnblogs.com/yanneu/p/6251892.html Recently, the teacher assigned a job, is to do a video-based vehicle detection and tracking, with about two weeks of time to do a simple, the effect is not ideal, but can not suppress some of their own knowledge to write down, here to put some blog on t

threshold value. This point is the corner point.To avoid calculating eigenvalues (time-consuming), use the following formula instead:The determinant of the Det matrix, traces of the trace matrix. It has been proved that the value of this equation is higher when two eigenvalues are high. The parameter k is generally set to 0.05~0.5.Harris Corner detection, can be improved by maximal value inhibition, that is, to ensure that the strength of the corner

I have previously introduced a Article on target detection using cascading classifier skip. We found that the Haar features in the library of opencv are only human faces, human organs, and human bodies. Recently, we wanted to perform a human hand detection. We used color features to make it very unreliable, try again with the Haar feature this time. In this cas

", cv_window_autosize); -Imshow ("Input Image", SRC); - - Mat DST, Dst_gray; +Resize (Src,dst,size ( -, -));//Change Size - + Cvtcolor (dst,dst_gray,color_bgr2gray); A atHogdescriptor Detector (Size ( -, -), Size ( -, -), Size (8,8), Size (8,8),9); -vectorfloat> descriptors;//histogram vector -Vectorlocations; -Detector.compute (Dst_gray, Descriptors,size (0,0), Size (0,0), locations); -printf"Number of HOG descriptors:%d", Descriptors.size ()); - inWaitkey (0); - return 0; to}Pedestrian

Pedestrian detection is a very hot and useful topic in the field of vision, especially in unmanned driving, the importance of pedestrian detection is self-evident.After the face detection, pedestrian detection is much simpler. The process is roughly the same as face detection