Image preprocessing grayscale space division method

A technology of image preprocessing and grayscale space, applied in the field of image processing, can solve problems such as increasing the complexity of solving problems, and achieve good segmentation effect and clear edge effect

Inactive Publication Date: 2016-02-03
CHENGDU RONGCHUANG ZHIGU SCI & TECH
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People hope to introduce some artificial knowledge-oriented and artificial intelligence methods to corr...

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  • Image preprocessing grayscale space division method
  • Image preprocessing grayscale space division method
  • Image preprocessing grayscale space division method

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[0031] All features disclosed in this specification, or steps in all methods or processes disclosed, may be combined in any manner, except for mutually exclusive features and / or steps.

[0032] The information in an image includes three parts: target object, background and noise. Image binarization is an image processing method to obtain the target object in the image. After binarization, all pixels in the image will be will change to white or black. When the image contains only two parts of information, the foreground and the background, the pixel value of the foreground can be set to 1, and the pixel value of the background can be set to 0, so that the image is binarized. There are many methods of binarization, generally divided into global threshold method and local threshold method

[0033] The global threshold method refers to a method that uses only one global threshold T in the binarization process. It compares the gray value of each pixel of the image with T, if it i...

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Abstract

The invention provides an image preprocessing grayscale space division method based on average filtering. The image preprocessing grayscale space division method comprises the following steps that weighted average operation is performed on three components in different weights according to the importance of RGB three components and other indicators; histogram correction is preferably performed by adopting histogram equalization, the histogram of an original image is corrected into uniform distribution by utilizing a grayscale transformation function, and then histogram equalization is performed; average filtering is performed on the image, a global threshold method is adopted, the method of one global threshold T is used only in the binarization process, the grayscale value of each pixel of the image is compared with T, and foreground color is taken if the grayscale value of each pixel of the image is greater than T; or background color is taken; and a center point P with the maximum number of corresponding pixels within L grayscale range acts as an initial class average value. Each pixel is inspected in the ith time of iteration, distance between each pixel and the average value of each grayscale is calculated, and the class, of which the average value is closest to the pixel, is assigned to each piexl. A new clustering center is calculated as for j=1,2,...l, the class average value is updated and all the pixels are inspected one by one.

Description

technical field [0001] The invention relates to the technical field of image processing, and provides a method for dividing gray space of image preprocessing based on mean filtering. Background technique [0002] Image segmentation is the technology and process of dividing an image into several specific regions with unique properties and proposing objects of interest. It is a key step from image processing to image analysis. The existing image segmentation methods are mainly divided into the following categories: threshold-based segmentation methods, region-based segmentation methods, edge-based segmentation methods, and segmentation methods based on specific theories. Since 1998, researchers have continuously improved the original image segmentation methods and applied some new theories and methods from other disciplines to image segmentation, and proposed many new segmentation methods. The objects extracted after image segmentation can be used in image semantic recogniti...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 张岱齐弘文
Owner CHENGDU RONGCHUANG ZHIGU SCI & TECH
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