High-definition color image segmentation algorithm

A color image and segmentation algorithm technology, which is applied in the field of image processing, can solve the problems of inability to obtain high-resolution images and complex principles, and achieve the effects of improving image segmentation accuracy, suppressing noise, and improving clarity

Pending Publication Date: 2022-02-25
GUANGXI NORMAL UNIV +2
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AI Technical Summary

Problems solved by technology

[0004] The current high-definition color image segmentation technology is complicated in principle and cannot obtain high-resolution images. Therefore, it is necessary to improve

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  • High-definition color image segmentation algorithm

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Embodiment 1

[0035] The present invention provides the following technical solutions: a high-definition color image segmentation algorithm, comprising the following steps:

[0036] A. Collect high-definition color images and store them;

[0037] B. Preprocessing the stored high-definition color images;

[0038] C. Train the preprocessed high-definition color image to obtain the trained high-definition color image;

[0039] D. Input the trained high-definition color image into the image segmentation neural network, and output the segmented high-definition color image.

[0040] In the present invention, the pretreatment method in step B is as follows:

[0041] a. Divide the pixels of the output image into several layers according to the brightness value. The brightness of each layer is different, and arrange each layer according to the brightness value from low to high, and the pixels in each layer The boundaries of the image are all composed of closed curves;

[0042] b. For the layer w...

Embodiment 2

[0046] A high-definition color image segmentation algorithm, comprising the following steps:

[0047] A. Collect high-definition color images and store them;

[0048] B. Preprocessing the stored high-definition color images;

[0049] C. Train the preprocessed high-definition color image to obtain the trained high-definition color image;

[0050] D. Input the trained high-definition color image into the image segmentation neural network, and output the segmented high-definition color image.

[0051] In the present invention, the pretreatment method in step B is as follows:

[0052] a. Divide the pixels of the output image into several layers according to the brightness value. The brightness of each layer is different, and arrange each layer according to the brightness value from low to high, and the pixels in each layer The boundaries of the image are all composed of closed curves;

[0053] b. For the layer with the lowest brightness and the layer with the highest brightnes...

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Abstract

The invention discloses a high-definition color image segmentation algorithm. The algorithm comprises the following steps: A, collecting and storing a high-definition color image; B, preprocessing the stored high-definition color image; C, training the preprocessed high-definition color image to obtain a trained high-definition color image; and D, inputting the trained high-definition color image into the image segmentation neural network, and outputting the segmented high-definition color image. The image segmentation algorithm adopted by the invention can improve the image segmentation accuracy, and can process images with multiple types, large data volume and multiple changes; according to the adopted image preprocessing method, the global brightness difference of the image is reduced, the image contrast is enhanced, the noise is effectively suppressed, the definition of the image is further improved, and the image segmentation precision is further improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a high-definition color image segmentation algorithm. 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. From a mathematical point of view, image segmentation is the process of dividing a digital image into mutually disjoint regions. The process of image segmentation is also a marking process, that is, the pixels belonging to the same area are given the same number. Image segmentation is a crucial preprocessing for image recognition...

Claims

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Application Information

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IPC IPC(8): G06T7/11G06T5/00G06N3/08G06N3/04
CPCG06T7/11G06N3/08G06N3/045G06T5/92G06T5/70
Inventor 李晟王秋玥阙涛涛
Owner GUANGXI NORMAL UNIV
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