Opencv is a free and open source C/C ++ library developed by Inter, Which is specialized in image processing and machine vision. Its full name is open source computer vision.
1. visual language MATLAB and opencv can be used for image processing. Which one is better?
MATLAB is a visual mathematical Processing Toolbox for scientific research in colleges and universities.
OpenCV Learning (Pixel operation manipuating the Pixels)
OpenCV Although there are many types of image processing functions, you can do a variety of common image processing, but there will always be some operations are not, then we need to manipulate the pixels, to achieve the functions we need. Today we will talk about several methods of
First, prefaceAfter two weeks of effort, while learning, while writing code, the initial completion of the system interface and some basic functions, including: 1 data read and write and display, and related basic operations (amplification, reduction and movement), 2 sample Data selection, 3 data normalization processing, 4 plotting spectral curve; 5 getting band information. The next work is to complete the remote sensing image classification of the
Python OpenCV learning notes histogram equalization, pythonopencv
This article introduces the histogram equalization of python OpenCV learning notes. The details are as follows:
Documents-https://docs.opencv.org/3.4.0/d5/daf/tutorial_py_histogram_equalization.html
Considering an image, its pixel value is limited to a s
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IntroductionCamshiftAlgorithmThat is, the "continuously apative mean-shift" algorithm is a motion tracking algorithm. It is used to track the color information of moving objects in video images. I divide this algorithm into three parts for ease of understanding:
Back Projection calculation.
Mean Shift Algorithm
Camshift Algorithm
1 Back Projection CalculationThe steps for calculating back projection are as follows:
1. Calculate the color histogram of the tracked
have been using QT+OPENCV development projects, while in VS directly lazy use precompiled OPENCV for development, resulting in the use of OpenGL prompts "No OpenGL support":
On the Internet, the reason is obvious because the precompiled library does not support OpenGL, so it is necessary to use CMake to rebuild the project. My development environment is: Win 8.1+VS2013+
Windows ms visual c ++ install opencv
DownloadOpencv installer and install it. I assume you have installed onto C:/program files/opencv.Setup ms visual c ++
I write details based on MS Visual Studio 2005. Follow menus of MS VISUAL C ++ window:
Tools> Options> projects and solutions> VC ++ directories>
Show directory for:> include files. Now addC:/Program Files/OpenCV/cv/includeC:/Program Files/
0. Preface
This article describes how to install OpenCV in the Raspberry Pi by compiling the source code, and a simple example of how to use OpenCV. For more information, please refer to-"Raspberry Pi Study notes-index Blog"1. Download several dependencies it is a good idea to update the Raspberry Pi software source before starting the installation. If the update time is too long, please refer to the blog p
In general, Python does not include the OpenCV module, need to install or configure their own, installation is relatively simple I will not say, say the download module, hands-on configuration (because the LZ is Winpython, green version of non-installation, although the integration of a lot of modules, but Wood has OPENCV, Can not be installed directly, can only be configured on their own)Then first of all
Label: Convert opencv image to video
I have explained the method and code for converting videos to images in opencv. This time, I want to explain how opencv converts images to videos:
Download the complete code in this article
1 videowriter description
Here we mainly use a class in opencv: videowriter
Its
OpenCV Learning notes: Templates match Java versionFirst of all, I want to correct a wrong learning habits, such as OpenCV large libraries, follow the official tutorial step-by-Step debugging learning efficiency is too low, opencv
Python OpenCV learning notes histogram reverse projection implementation, pythonopencv
This article introduces the implementation of the reverse projection of the python OpenCV learning note histogram. The details are as follows:
Documents-https://docs.opencv.org/3.4.0/dc/df6/tutorial_py_histogram_backprojection.html
I
Recently in the process of learning OpenCV, found a very good book "Mastering OpenCV with practical Computer Vision". In this book, the author explains how to use OPENCV (c + + version) in Practical computer vision projects in a very understandable way. Unfortunately, there is no Chinese version of the book so far. So
I haven't made a summary for a while. I don't know what I'm busy with every day! Now it takes an hour to summarize the learning in the last few days.
Edge detection technology is the first step in image analysis. It uses the extreme values of the first derivative of the image or the zero point information of the second derivative to extract the edge.
To put it simply, it is the problem of gray-scale image changes. In some places, image changes are slo
getHistogram(const cv::Mat image) ; cv::SparseMat getSparseHistogram(const cv::Mat image) ;private: int histSize[3]; float hranges[2]; const float* ranges[3]; int channels[3];};Two functions Gethistogram and Getsparsehistogram are implemented here. The only difference is that Getsparsehistogram returns a sparse matrix.Cv::matnd Colorhistogram::gethistogram (const Cv::mat image) {Cv::matnd hist; Compute histogram cv::calchist (image, 1,//histogram of 1 image only channels,
OpenCV Learning (calculate the histogram of images)OpenCV calculates the histogram of the image
Calculating the histogram of an image is a very common operation in the field of image processing. OpenCV provides the calcHist function to calculate the image histogram. However, this function is quite difficult to tell the
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 feature point detection algorithms, and can b
information is discarded in grayscale mode, the original transparent pixel value becomes 0, it becomes black (255 is white)Three, the output picture We got a gray picture, what should we do if we want to save it? At this point you need to use the imwrite () function, Ipython input help (Cv2.imwrite), get:imwrite (...) Imwrite (filename, img[, params]) , retvalFileName is the name of the output image, IMG is the image to be exported, and the params is the parameter of the picture format, and re
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