opencv image recognition

JAVA+OPENCV Color Recognition Recently in the project involved in the image recognition, the use of third-party detection is OPENCV, in view of the online use of Java to do a very small amount of information, so I wrote this blog, I hope the students a little help later!No

The contours in the OpenCV21.1 Initial Knowledge ContourGoal? Understand what outlines are? Learn to look for outlines, draw outlines, etc.? Function: Cv2.findcontours (), cv2.drawcontours ()21.1.1 what is a contourA contour can be simply thought of as a curve that connects successive points (contiguous boundaries) with the same, color, or grayscale. Profiles are useful for shape analysis and object detection and recognition.? To be more accurate, use

OpenCV is an open source computer graphics and image Library developed in C/s + +, very powerful and complete in research materials. The focus of this article is to describe how to use PHP to invoke local functionality. Face detection technology is just a branch of OPENCV application. 1. Installation Compiled from the source code into a dynamic so file. 1.1. Inst

KNN is a simple algorithm used to classify data mining, which is used to realize the simple recognition of 4 flowers in this cluster.Environment: PYTHON2.7+OPENCV3.0+WINDOWS10Principle: After the use of KNN function to extract 4 flower feature points, the need to identify the image to extract the signs points, and the gallery of 4 flowers, compared to the category of the most matching points are considered

First, preface This article refers to the automatic license plate recognition project in the deep understanding of OPENCV practical Computer Vision Project analysis, and then carries on the practice after understanding the method. The difficulty of accurately identifying the sequence of the characters in the license plate area is to realize the exact location of the license plate area. So the final

samples were generated by random andother pictures is used for training Sampls. After time of the random checkout,the highest identification probability can be 93%, which are acceptable for ourdaily use.Furter Works can aim atthe better efficiency of ROI extraction and grouping, plastic bags is terriblefor texture feature Extraction, testing on texture generated a bad result. Ifwe can remove the influence of plastic bags, I think texture features would giveus some interesting results.Reference:

This article was reproduced from: http://blog.csdn.net/ap1005834/article/details/51340831 First, preface This article refers to the automatic license plate recognition project in the deep understanding of OPENCV practical Computer Vision Project analysis, and then carries on the practice after understanding the method. The difficulty of accurately identifying the sequence of the characters in the license p

Python + opencv for Dynamic Object Recognition, pythonopencv Note: This method is very affected by light changes. Figure of the result of your mobile phone shaking at home: Source code: #-*-Coding: UTF-8-*-"Created on Wed Sep 27 15:47:54 2017 @ author: tina" import cv2 import numpy as np camera = cv2.VideoCapture (0) # parameter 0 indicates the first camera # determine whether the video is enabled if (came

scale space. As shown in the following: 　　　　 The author of this algorithm gives the empirical value of the SIFT parameter in the article: octaves=4 (reduce the size of the image by reducing the sampling, and make up the image pyramid with reduced size (4 layers)? ), the scale space is 5, that is, each size uses 5 different variance of the Gaussian core for convolution, the initial variance is 1.6, and so o

Busy for the most part of the semester fingerprint, palm processing, here a little to sort out someGoal Find the center point and Triangle Point of fingerprint image, count the number of interval ridge lines, complete the fingerprint classification. Function The processing that needs to be done includes: Segmentation foreground and background (using gradient map, direction field realization); Enhanced fingerprint

Statement:This article only records my thoughts on how to process the image recognition process of the 163 album Verification Code. It is only for technical purposes. Therefore, no source code download is provided in this Article !! I am not responsible for any liability arising from any use of the methods described here !! If you need to reprint this article, please indicate the original author and source

Image Recognition in various recognition Libraries In-Spirit Eugene zatepyakin open source stuff Http://code.google.com/p/in-spirit/w/list Face Recognition Http://code.google.com/p/vjdetector/ Flash Kinect Http://code.google.com/p/as3openni/ Face-recognition-library-as3

different data bits does not exceed 5, the two images are very similar. If the number is greater than 10, the two images are different.You can put several images together and calculate their Hamming distance comparison to see if the two images are similar.The advantage of this algorithm is that it is simple and fast, and is not affected by the image size scaling. The disadvantage is that the image content

[OpenCV] video reading and some simple image processing, opencv reading1. Preface As a computer image processing tool, openCV began to show some irreplaceable advantages due to free disclosure, copyright, and so on (it has been shown for a long time ). Well, I have been work

\ opencv \ build \ include) (Connector-additional library directory = D: \ opencv248 \ opencv \ build \ x86 \ vc11 \ Lib, vc11 corresponds to vs2012, other versions, and so on) 　　　　 5. Save and compile. After compilation, run the prompt that the dll library (Runtime Library File) cannot be found ). You can add environment variables. Add system variables (; Path = D: \ opencv248 \

Public platform Message Interface Development image recognition-face recognition I. Preface In the past few small applications, it seems that the response is not cool or hot, and everyone is not interested. Today, we will give you a bright eye: face recognition on the public platform. Some time ago, I saw a report on

Well-written SVM + hog Classifier Training Class mysvm: Public cvsvm {public: int get_alpha_count () {return this-> sv_total;} int get_sv_dim () {return this-> var_all;} int get_sv_count () {return this-> decision_func-> sv_count;} double * get_alpha () {return this-> decision_func-> alpha;} float ** get_sv () {return this-> Sv;} float get_rov () {return this-> decision_func-> rho;}}; void train () {char classifiersavepath [256] = "C: /pedestrianDetect-peopleFlow.txt "; string positivepath =" E

Java fingerprint recognition + Google Image Recognition Technology Some time ago, when I saw this similar image search principle blog on Ruan Yifeng's blog, there was an impulse to implement these principles. I wrote a demo of image

PS. Due to the limited length of the CSDN blog post, some of the content in this article has been cut off.On the wiki of OpenCV Chinese website, there is a more readable and complete version, welcome to browse. OpenCV Wiki: Introduction to OpenCV programming (basic read and write operations of matrix/image/Video) Int

As follows: # Import UIImage + OpenCV. h # import MyViewController. h # import # Import # Import # Import # Import // Aperture value to use for the Canny edge detectionconst int kCannyAperture = 7; @ interface MyViewController ()-(void) processFrame; @ end @ implementation MyViewController @ synthesize imageView = _ imageView; @ synthesize imageView1 = _ imageView1;-(void) viewDidLoad {[super viewDidLoa