Image Processing

【Image processing】Color space transformation

color space transformation 1. Introduction [​ A general image has three channels] : red (R), green (G), and blue (B) . Each channel is composed of (0-255) different values, which constitute a colorful image, which is called the image color space. In image processing, there are additional color spaces (such as HSV, HIS), which are …

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Threshold Transformation of MATLAB Image

Let’s introduce how to use the threshold transformation method in [MATLAB] to convert the original image into a binary image. The so-called binary image, that is, only black and white pixels, are as follows: Open the MATLAB software and write the following code in the editor of its main interface: I=imread('G:\MATLAB\bm.bmp'); %Read the picture in …

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Realization of Recognition and Tracking of Moving Objects with MATLAB

I have to say that [MATLAB] has a lot of image processing functions, but the speed is sometimes surprisingly slow. I still want the pointer of c, although it is a bit dangerous, but the speed is great. The second MATLAB program, the recognition and tracking of moving objects. Here we mainly use the frame …

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Python crawls Instagram data & Python converts pictures to text

#-*- coding:utf-8 -*- import pytesseract from PIL import Image # Use pytesseract to recognize English print (pytesseract.image_to_string(Image.open( 'textEng.png' ))) # Use pytesseract to recognize Chinese print (pytesseract.image_to_string(Image.open( 'textCh.png' ), lang = 'chi_sim' )) # Use pytesseract to recognize Chinese and English (the function parameters used are the same as above, Chinese is compatible with English) …

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Image processing based on dark channel dehazing (XD digital signal processing major work)

Image processing based on dark channel dehazing XD ‘s digital signal processing work The specific code and PPT can be downloaded here: /download/yifantan/72862665 Image processing : Dehaze the images with unrecognizable details when shooting in dense fog to restore clearer and more realistic images. In real life, it is of great significance to the application …

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Image Neighborhood Processing in MATLAB

Let’s introduce how to process the neighborhood of the image in [MATLAB . The specific steps are as follows:] First open MATLAB and write the following code in the editor of its main interface: M=imread('G:\MATLAB\bm.bmp'); %Read the picture in the current path I = rgb2gray(M); % to grayscale g=inline('max(x(:))'); B=nlfilter(I,[3 3],g); % Neighborhood processing figure,imshow(I); …

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Image Indexing and Dithering Conversion in MATLAB

Let’s introduce how to perform image indexing and dithering conversion in [MATLAB] , which is a very classic operation for instantiated output of images, as follows: Open the MATLAB software and write the following code in the editor of its main interface: RGB=imread('peppers.png'); [X,map]=rgb2ind(RGB,256); I=dither(RGB,map); BW=dither(I); % Display the index image as shown in figure1. …

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How to batch process the size of images in MATLAB Technical Salon

Let’s introduce how to batch uniformly process the size of multiple images in [MATLAB] , provided that they are located in the same folder path, as follows: Open the main interface of MATLAB, and write the following code in the main interface of its editor: file_path = 'D:\dyq1995\dyq\';% The path of the image folder to …

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