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Method of image segmentation based on area upgrowth and ant colony clustering

A technology of region growing and image segmentation, which is applied in image enhancement, image data processing, character and pattern recognition, etc., and can solve problems such as long convergence time

Inactive Publication Date: 2008-10-15
NORTHWESTERN POLYTECHNICAL UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing ant colony algorithm has too long convergence time in the application of image segmentation, and it is easy to fall into local optimum.

Method used

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  • Method of image segmentation based on area upgrowth and ant colony clustering
  • Method of image segmentation based on area upgrowth and ant colony clustering
  • Method of image segmentation based on area upgrowth and ant colony clustering

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Embodiment Construction

[0038] The present invention will be further described now in conjunction with accompanying drawing:

[0039] First of all, since the premise of consideration is to grow from the pixel with the highest gray value, it is very important to remove the noise in the image. Therefore, the median filter of the four neighborhoods is used to filter out the noise; then, the pixel with the largest gray value is selected as the seed point for region growth. Then, a new guide function is defined by using the spatial information and gray information mentioned after the region growing, and it is used in the ant colony algorithm to perform clustering and merging between regions to obtain the final segmentation result.

[0040] Since the premise of consideration is to grow from the pixel with the highest gray value, it is very important to remove the noise in the image. Considering that only some noise points with abnormal gray values ​​(high or low) need to be removed, the median filter of t...

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Abstract

The invention relates to an image segmentation method based on regional growth and ant colony clustering, which is characterized in that: the premise of the consideration is that the growth starts from a pixel with highest gray value, so the removal of noise from an image is very important. Therefore, the four-neighborhood middle value filtration is adopted for filtering the noise; and the pixel with the maximum gray value is taken as a seed point to carry out the regional growth; then, a new guide function is defined by utilizing spatial information and gray information extracted after the regional growth to be used in the ant colony algorithm for carrying out the cluster merging in the regions, thus obtaining the final segmentation result. The image segmentation method based on regional growth and ant colony clustering proposed by the invention has three evident advantages: firstly, the shortcoming of not being able to obtain the meaningful region from the regional growth is overcome; secondly, the searching time of the ant colony clustering algorithm is greatly improved; thirdly, the definition of the new guide function can accurately and effectively guide the ant colony clustering and improve the accuracy of the image segmentation.

Description

technical field [0001] The invention relates to an image segmentation method based on region growth and ant colony clustering, and belongs to the fields of computer vision, image understanding, pattern recognition and artificial intelligence. Background technique [0002] Image segmentation refers to the technology and process of dividing an image into regions with different characteristics and extracting objects of interest. Image processing after segmentation, such as feature extraction and object recognition, all depend on the quality of image segmentation, so image segmentation has always been a research hotspot in the field of computer vision and pattern recognition. [0003] At present, a variety of methods have been proposed to be applied to the field of image segmentation, such as threshold method, edge detection method, mathematical morphology method, region-based processing method, etc. These methods have achieved good results for different images. However, for di...

Claims

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Application Information

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IPC IPC(8): G06K9/34G06K9/62G06T5/00
Inventor 郭雷杨卫莉赵天云肖谷初
Owner NORTHWESTERN POLYTECHNICAL UNIV
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