opencv image recognition

Reprint: Https://mp.weixin.qq.com/s/J6eo4MRQY7jLo7P-b3nvJg Li Lin compiled from PyimagesearchAuthor Adrian rosebrockQuantum bit Report | Public number Qbitai OpenCV is a 2000 release of the open-source computer vision Library, with object recognition, image segmentation, face recognition, motion

best interpolation function sin (x) x, whose mathematical expression is:The grayscale value of the pixel (x, y) to be determined is interpolated by a weighted interpolation of 16 gray values around it, such as:The grayscale calculation for the pixel to be obtained is as follows:f (x, y) = f (i+u, j+v) = ABCwhichThe three-time curve interpolation method is computationally large, but the image after interpolation is the best.V. Comprehensive examplesVI

Java-based OPENCV implementation of Digital Image recognition (I.)Recently assigned to a task, to do digital recognition, I assign the task is to separate the numbers, then a face confused, direct Baidu Java How to divide the figures in the picture, and then Baidu to use BufferedImage this class to operate; Try to do a

Java-based OPENCV for digital image Recognition (ii)-Basic flowBefore we do a project, we should have a general grasp, or a progress bar, to step by push us to complete the project, before we formally start, we first discuss the process.The main thing I do is identify the numbers in the table, but that's not the point. The point is that through this we can extrap

in polar coordinates to the polar angle plane, we will get a sine curve. For example, for a given point and we can draw (in plane-):Only points and that meet the following conditions are plotted. We can do this for all the points in the image. If two different points do this, the resulting curves in the plane-intersect, which means they pass the same line. For example, following the example above we continue to point to:, and point, Draw, get:The t

are in the same order.*/int index = 0;for (int i=0;i{PData = mask.ptrfor (int j=0;j{if (pdata[j]==0)rst[index++]= ' 0 ';Elserst[index++]= ' 1 ';}}return rst;}void Photofingerprint::insert (Mat src,string val){String strval = HashValue (src);M_hashmap.insert (paircout}void Photofingerprint::find (Mat src){String Strval=hashvalue (SRC);Hash_mapif (It==m_hashmap.end ()){coutElsecout/* Return *it;*/}int Photofingerprint::D istance (String str1,string str2){if ((Str1.size ()!=64) | | (Str2.size ()!=

' Correlation ' for values with time-series relationships' Hamming ' only for binary data2. ' Start ' (initial centroid position selection method)' Sample ' randomly selects a k centroid point from X' Uniform ' randomly generates K centroid based on an evenly distributed range of XThe ' cluster ' initial cluster stage randomly selects a sub-sample of 10% X (this method initially uses the ' sample ' method)Matrix provides a k*p of matrices as the initial centroid position set3. ' Replicates ' (nu

information of the keyboard The following function is to identify the coordinates of the cipher keyboard by means of an image recognition method. The password keyboard encountered is shown in the following figure There is also the contents of the input box, I have to intercept. Solution idea: 1, image recognition, a

offset=point ());PTS: A polygon fixed-point set.NPTs: The number of vertices of the polygon.Ncontours: The number of polygons to draw.Offset: An optional offset for all point outlines.#include String words= "A simple example"; Puttext (SRC, words, point (SRC.ROWS/2,SRC.COLS/4), Cv_font_hershey_complex, 1, Scalar (255, 0, 0)); Namedwindow ("Display word"); Imshow ("Display word", SRC); Point Center = point (300,200); int r = N; Circle (Src,center,r,scalar (0,0,0));

It can be said that from the beginning of this article, the end of the basic image recognition, came to the second stage of learning. In peacetime processing two value image, in addition to some of the morphology of the operation, there is a section of the contour connected area perimeter mark, there is one of the most common is the filling of the hole,

call in OpenCV is the following function, which is convenient(1) It is usually used to increase the global contrast of many images, especially when the contrast of useful data of an image is quite close.(2) Brightness can be better distributed on the histogram. This can be used to enhance the local contrast without affecting the overall contrast, histogram equalization by effectively extending the common b

The technology introduced in this article is not original, but learned from a German named Robert Isele. He wrote a PHP extension openCV, which encapsulates only two functions, face_detect and face_count. OpenCV is an open-source computer graphics image library developed with C/C ++. it is very powerful and has a complete set of research materials. This article f

This article from http://blog.csdn.net/hellogv/, reference must indicate the source! The last time I talked about how to port opencv1.10 on WinCE/Wm, this time I will talk about how to use open1.10 after cropping and porting on WM mobile phones, and use opensurf on opencv (the address of opensurf in googlecode: http://code.google.com/p/opensurf1/), let's take a look at the program running this article: The left is the feature points found by the surf

of vertical bars on each dimension. Ranges: The range used for statistics. For example, float rang1[] = {0, 20};float rang2[] = {30, 40}; Const float*rangs[] = {rang1, rang2}; Then the values for the 0,20 and 30,40 ranges are counted. Uniform: Whether the width of each vertical bar is equal. Accumulate: Whether or not to accumulate. If true, Hist will not be emptied first at the next calculation. Draw a line, draw a color in the image img, the

Then the image of the previous grayscale processing, the next gray image color recognition, my method is relatively simple, there are other good methods can be put forward, we progress together. Objective: Turns the pixel grayscale in all of the grayscale images to white (set to 255), and less than 128 to black (set to 0). Then count the number of black and white

thresholds is discussed in the extension), according to the high threshold is worth an edge image, such an image contains very few false edges, but because the threshold is high, the resulting image edge may not be closed, the problem is not resolved to use another low threshold value. Popular: Is in the edge detection, or to use the filter to reduce noise, firs

Described earlier how to bulk read the picture, so there will also be a batch of display of pictures, then in peacetime we show the picture, will find a picture a window, will come out a lot, this time will think of MATLAB we will often use subplot display multiple pictures in a window, Before http://blog.csdn.net/qq_20823641/article/details/51910066 This article also provides a method, can refer to, after further study, from simple to complex, once again think subplot (), Feeling more and more

Opencv handwritten multiple choice question marking (2) Character Recognition and opencv Character Recognition Opencv handwritten multiple choice question marking (2) Character Recognition Generally, you only need to identify ABCD

The story of face recognition can't be told. Let's leave the investigation to everyone. Here we are talking about face recognition with opencv. Because it is real face recognition and not funny entertainment, the database must be powerful. We recommend a website http://www.face-rec.org/databases /. Here is an overview

Opencv achieves character segmentation for License Plate Recognition, opencv license plateIntroduction In the previous article, we have located the license plate number in the image, copied the license plate number into a new image, and displayed it, this chapter continues t