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Gray threshold acquisition method and image segmentation method based on adaptive genetic algorithm

A technology of grayscale threshold and genetic algorithm, which is applied in the field of image processing, can solve problems such as complex algorithms, and achieve the effects of precise image analysis, accurate and efficient image segmentation, and high robustness

Active Publication Date: 2021-07-20
广东唯仁医疗科技有限公司
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Problems solved by technology

This image segmentation method combines BP neural network technology and adaptive genetic algorithm technology for image segmentation, but the algorithm is complex

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  • Gray threshold acquisition method and image segmentation method based on adaptive genetic algorithm
  • Gray threshold acquisition method and image segmentation method based on adaptive genetic algorithm
  • Gray threshold acquisition method and image segmentation method based on adaptive genetic algorithm

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Embodiment Construction

[0040] The following are specific embodiments of the present invention and in conjunction with the accompanying drawings, further describe the technical solution of the present invention, but the present invention is not limited to these descriptions, but the present invention is not limited to these embodiments.

[0041] Parallel region segmentation technology is a technology that detects regions of interest in a parallel manner to segment images. First of all, for a grayscale image, this technology will classify all pixels into two categories according to a predetermined grayscale threshold within the grayscale value range of the image, and the pixels whose grayscale value is greater than the grayscale threshold are classified into one category. Pixels whose grayscale value is less than the grayscale threshold are classified into another category, and pixels whose grayscale value is equal to the grayscale threshold can be classified into any one of the first two categories de...

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Abstract

The invention relates to a method for acquiring a gray threshold value and an image segmentation method based on an adaptive genetic algorithm, and belongs to the technical field of image processing. The method for obtaining the gray threshold value of the present invention comprises the following steps: S01, performing population initialization on the gray value of the image; S02, calculating the fitness value of the individual in the population; S03, performing a selection operation and updating the population; S04, calculating the crossover probability of the individual, Perform the crossover operation according to the crossover probability, and update the population; S05, calculate the mutation probability of the individual, perform the mutation operation according to the mutation probability, and update the population; S06, judge whether the termination condition is satisfied, and if so, obtain the optimal solution and obtain the optimal gray degree threshold; otherwise, execute step S02. The image segmentation method of the present invention performs image segmentation according to the gray threshold acquired by the above gray threshold acquisition method. The invention has self-learning, self-adaptability and high robustness, and can concurrently solve the gray threshold value from the whole world, better avoid the local optimal value, and is accurate and efficient.

Description

technical field [0001] The technical field of image processing of the present invention relates in particular to a method for acquiring a gray threshold value and an image segmentation method based on an adaptive genetic algorithm. Background technique [0002] Image processing is essentially the act of processing image information to meet people's visual psychology or application needs. Image segmentation is a kind of image processing technology, and its purpose is to divide the image into regions with different characteristics and extract the parts of interest to meet people's certain needs. In recent years, the research on image segmentation has always been a hot spot in the research center of image processing technology. People's attention and investment in it have been increasing. It is an important image analysis technology and a key step from image processing to image analysis. [0003] Image segmentation methods mainly include edge detection segmentation, region seg...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/11G06T7/136G06N3/12
CPCG06N3/126G06T7/11G06T7/136
Inventor 安林秦嘉李鹏
Owner 广东唯仁医疗科技有限公司
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