- nine trillion and seven hundred and eighty-seven billion thirty million two hundred and forty thousand eight hundred and seventy-three 
- do person
- Sun Jixiang 
- set price
- RMB 35.00
- book name
- image processing
- Publication time
- November 2009
- open book
- 16 open
- Science Press
Python + opencv real timeimage processing2020-01-04 23:09:35Beginner opencvimage processingMy friends must have a headache about Gaussian function, filtering, threshold binarization and other features. Here is a small project for you to share, which can be dynamically viewed in real time through the cameraimage processingIt can also be helpful for you to adjust parameters and test.
[Pythonimage processing]Iimage processingBasic knowledge and opencv entry function2018-08-16 22:54:17This series of articles is about Python OpenCVimage processingKnowledge. In the early stage, it mainly explains the introduction to images, the basic usage of OpenCV, and in the middle stageimage processingVarious algorithms, including image sharpening operator, image enhancement technology, image segmentation, etc. in the later stage, combined with deep learning, research on image recognition and image classification application
This series of articles is to explain Python OpenCV image processing knowledge. In the early stage, it mainly explains the introduction of image and the basic usage of OpenCV. In the middle stage, it explains various algorithms of image processing, including image sharpening operator, image enhancement technology, image segmentation, etc. in the later stage, it studies image recognition and image classification application in combination with in-depth learning. I hope the article is helpful to you. If there are deficiencies, please forgive me~
As the first article, this article will explain the basic knowledge of image processing and the introduction function of OpenCV. The knowledge points are as follows:
- 1. Basic knowledge of image
- 2. Opencv reading and writing images
- 3. Opencv pixel processing
PS: the article also learned the knowledge of Netease cloud Gordon education. I recommend you to study.
All source code of this series in GitHub:
PS: ask for help to order a star. Haha, I will share more codes in the future when I use GitHub for the first time. Come on.
At the same time, the author's C + + image series knowledge is recommended:
image processingMATLAB image reading2017-05-29 12:50:45Speaking ofimage processing, the first step is image reading. Matlab is the simplest imread function. This section introduces the usage of imread and its error prone places
When it comes to image processing, the first step is image reading. Matlab is the simplest imread function. This section introduces the usage of imread and its error prone places
As shown in the figure above, imread includes the above usages in MATLAB documents, but it is not required to master them all. I think I can use one or two, and I can understand the syntax of others.
Let's introduce the most commonly used statement a = imread (filename)
Let's read a picture
>>A = imread ('stare. JPG '); >> imtool(a)
As shown in the figure, first note that the syntax is correct, a = imread ('stare. JPG ');
1、 Correct demonstration.
He means to read the image data named "gaze. JPG" in the current path into a and save it. Then we can see that there are some data in the workspace area on the far right of the image. This is the data of A. We can see that the image is 340five hundred and ninety-three3 size, which means 340 rows, 593 columns, 3-channel (RGB) pictures. Uint8 on the right represents an 8-bit unsigned integer type（ The following imtool statements are used to display images, which will be discussed in detail later)
Add a little knowledge:
To clear the command window, enter the command CLC
To clear the workspace, enter the command clear
To close all open windows, enter the command close all
To view image information, use whos
2、 Stepping pit
Well, now that we know the correct way to write, let's try what pit there is（ Daring to try and make mistakes is an excellent quality in this business)
1. Why semicolon?
Because matlab compiles line by line, line by line. If you don't write well, you will directly get the compilation results. Just show you an example.
An A and B matrix are created above. The a matrix does not end with a semicolon. The window directly displays the content, while the B matrix uses a semicolon and does not display the content. However, we can see that after compilation, two array matrices have been created in workspace. We can also see that there are specific data at the top by clicking the variable name. Similarly, if we read the picture a = imread ('staring. JPG ') without writing a semicolon, a large wave of data will appear in the window and jump out. It's sour and cool. Those data are the pixels saved in the array.
If you don't write the variable name, such as > > imread ('staring. JPG '); It gives you a name by default: ANS
When you want to rewrite a sentence that is the same or similar to the above, you can press the up arrow button on the keyboard
This shortcut can help you quickly modify the sentence, easy to use.
2. English half angle symbol
Everyone who has learned programming should know it. Don't use the whole Chinese. ", Don't use the English full angle symbol "." as for why, I don't know. Matlab will appear: file "stare. JPG" does not exist
This is a common mistake. You remember that you have the picture and the name of the picture, but you don't put it in the current path. How do you ask others to find it? MATLAB is not so powerful that you can search all the picture files in your computer. Similarly, the compiler will appear: does not exist. But there are remedies. You can indicate where you can find them, for example:
I put the picture "gazing. JPG" under the build file on disk D, and the results kept making mistakes, as shown in the figure. At first glance, I found that gazing was written as gazing. Then, I wrote build as bulid. Ha ha, I'm just a beginner. I make mistakes when I'm careless. This also shows that I really have to concentrate on writing code. This bug is easy to change, But if you do a big project, write hundreds of thousands of lines of code, and spend hours because of spelling mistakes, it's a big loss.
Well, the reading and writing of this document is written here. If you have any questions, you can comment on your discussion and study together. Maybe we will have a spark of thought. It may be trivial and simple. As long as it can give you a little harvest, this blog will be valuable. The next section continues with other functions. Thanks for watching
Welcome to my official account [CV], learning and communicating.
Do it in Pythonimage processing2007-10-28 23:45:00Do it in Pythonimage processingRecently, I'm doing something more evil - verification code recognition to learn some new skills. Because I'm a beginner, rightimage processingI don't know much about it. If you want to benefit me, you must benefit my tools first. Since it's just an experiment, use Python for prototype development, and thenImage processing with PythonRecently, I'm doing something more evil - verification code recognition to learn some new skills. Because I'm a beginner, I don't know much about image processing. If I want to benefit my things, I must first benefit my tools. Since I'm just doing an experiment, it's better to use Python for prototype development. In Python, the commonly used image processing library is PIL (Python Image Library). The current version is 1.1.6, which is very convenient to use. You can http://www.pythonware.com/products/pil/index.htmDownload and learn.Here, I mainly introduce some functions provided by PIL that may be used in image recognition, such as image enhancement and filtering. Finally, the advantages and disadvantages of using Python for image processing and recognition are given.Basic image processingImport image module is required before using PIL:import ImageThen you can use image. Open ('xx. BMP ') to open a bitmap file for processing. When you open a file, you don't have to worry about the format or understand the format. No matter what format, just throw the file name to image.open. It's really called BMP, JPG, PNG, gif... None of them can be missing.img = Image.open(‘origin.png’) # Get the instance object img of an imageFigure 1 originalIn image processing, the most basic is the conversion of color space. Generally speaking, our images are in RGB color space, but in image recognition, we may need to convert the image to different color spaces such as gray image and binary image. PIL also provides very complete support in this regard. We can:new_ img = img.convert(‘L’)Convert img to 256 gray level image. Convert () is a method of image instance object. It accepts a mode parameter to specify a color mode. The values of mode can be as follows:· 1 (1-bit pixels, black and white, stored with one pixel per byte)· L (8-bit pixels, black and white)· P (8-bit pixels, mapped to any other mode using a colour palette)· RGB (3x8-bit pixels, true colour)· RGBA (4x8-bit pixels, true colour with transparency mask)· CMYK (4x8-bit pixels, colour separation)· YCbCr (3x8-bit pixels, colour video format)· I (32-bit signed integer pixels)· F (32-bit floating point pixels)How's it going? Isn't it rich enough? In fact, PIL also supports the following rare color modes: La (L with alpha), rgbx (true colour with padding) and RGBA (true colour with premultiplied alpha).Let's take a look at the image converted when the mode is' 1 ',' l 'and' p ':Figure 2 mode = '1'Figure 3 mode = 'l'Figure 4 mode = 'p'The convert () function also accepts another implicit parameter matrix, which is a tuple with a length of 4 or 16. The following example is an example of converting RGB space to CIE XYZ space:rgb2xyz = (0.412453, 0.357580, 0.180423, 0,0.212671, 0.715160, 0.072169, 0,0.019334, 0.119193, 0.950227, 0 )out = im.convert("RGB", rgb2xyz)In addition to the complete color space conversion capability, PIL also provides functions such as resize() and rotate() to obtain geometric transformation capabilities such as changing size and rotating pictures. In terms of image recognition, image examples provide a histogram() method to calculate histograms, which is very convenient and practical.image enhancementImage enhancement is usually used for preprocessing before image recognition. Appropriate image enhancement can make the recognition process get twice the result with half the effort. In this regard, PIL provides a module called imageenhance, which provides several common image enhancement schemes:import ImageEnhanceenhancer = ImageEnhance.Sharpness(image)for i in range(8):factor = i / 4.0enhancer.enhance(factor).show("Sharpness %f" % factor)The above code is a typical example of using the imageenhance module. Sharpness is a class of the imageenhance module to sharpen images. The first mock exam module includes the following categories: Color, Brightness, Contrast and Sharpness. They all have a common interface. Enhance (factor), which accepts a floating-point parameter factor to indicate the enhanced proportion. Let's take a look at the effects of these four classes under different factorsIn Figure 5, color is used for color enhancement, the factor value is [0,4], and the step is 0.5Fig. 6 enhance the brightness with birghtness, factor value [0,4], step 0.5Fig. 7 contrast is enhanced with contrast, factor value [0,4], step 0.5Figure 8 sharpen the image with sharpness, factor value [0,4], step 0.5Image filterPIL's support for filter is very complete. In addition to common blur, relief, contour, edge enhancement and smoothing, as well as median filter and modefilter, it's so convenient that you can make your own Photoshop. These filters are placed in the imagefilter module. Imagefilter mainly includes two parts: one is the built-in filter, such as blur and detail, and the other is the filter function, which can specify different parameters to obtain different effects. Examples are as follows:import ImageFilterim1 = im.filter(ImageFilter.BLUR)im2 = im.filter(ImageFilter.MinFilter(3))im3 = im.filter(ImageFilter.MinFilter()) # same as MinFilter(3)You can see that the use of the imagefilter module is very simple. Each filter only needs one line of code to call, and the development efficiency is very high.Figure 9 using blurFigure 10 using contourFigure 11 using detailFigure 12 use EMBOSSFigure 13 using edge_ ENHANCEFigure 14 using edge_ ENHANCE_ MOREFigure 15 using find_ EDGESFigure 16 using SharePointFigure 17 using smoothFigure 18 using smooth_ MOREThe above are the effects of several built-in filters. In addition, imagefilter also provides some filter functions. Let's take a look at the effects of these filters that can change their behavior through parameters:Figure 19 using kernel (), parameters: size = (3, 3), kernel = (0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5)Figure 20 using maxfilter, default parametersFigure 21 using minfilter, default parametersFigure 22 using medianfilter, default parametersFigure 23 using modefilter, parameter size = 3Figure 24 uses rankfilter with parameters size = 3 and rank = 3SummarySo far, the introduction to PIL has come to an end. In general, PIL has built-in strong support for image processing and recognition. From various enhancement algorithms to filter, people can't doubt the feasibility of using python. The only disadvantage of Python is that the execution time is too slow, especially when implementing some algorithms with large amount of computation, it requires great patience. I once used Hough transform to find straight lines in an image. It takes a few seconds for a pure Python implementation to process a 340 * 100 image (P4 3.0g + 1G memory). However, using PIL does not need to pay attention to image format, built-in image enhancement algorithm and filter algorithm. These advantages make Python suitable for constructing prototypes and experiments. In these two aspects, Python is more convenient than MATLAB. For the development of commercial image recognition products, the open source c + + library Gil from adobe, which has been boost accepted, can be considered to give consideration to both execution performance and development efficiency.
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