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Method of multi-formwork image segmentation based on ant colony clustering

An image segmentation, multi-template technology, applied in image analysis, genetic model, image enhancement and other directions, to achieve better results, improve segmentation accuracy and accuracy, and reduce the effect of noise

Inactive Publication Date: 2011-03-16
BEIHANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] The present invention proposes a multi-template image segmentation method based on ant colony clustering, the purpose of which is to provide an effective way to solve the problem of image segmentation, and can also be applied to other complex intelligent optimization problems

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  • Method of multi-formwork image segmentation based on ant colony clustering
  • Method of multi-formwork image segmentation based on ant colony clustering
  • Method of multi-formwork image segmentation based on ant colony clustering

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Embodiment Construction

[0098] Next, a specific example is used to verify the performance of the multi-template image segmentation method based on ant colony clustering proposed by the present invention. A 570*447 image in jpg format is used as the verification object. The experimental environment is P43.06Ghz, 1G memory, MATLAB7.1 version, the specific implementation steps are as follows:

[0099] Step 1: Image preprocessing

[0100] (1) Read the image and convert it to a grayscale image

[0101] The verification object is converted into a grayscale image and then edge segmented, which makes the processing method uniform and easy to program and design.

[0102] (2) Image size adjustment

[0103] Adjust it to a suitable size before subsequent processing, saving time and improving the effect.

[0104] (3) Median filtering to remove noise and image sharpening

[0105] Image denoising, reducing the influence of noise during image segmentation; image sharpening, making the edge features of the image ...

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Abstract

The invention provides a multi-templet image separation method based on Ant Colony Clustering. The multi-templet separation method comprises the implementation steps as follows: step 1. image preprocessing; step 2. determining the attributes of each pixel with such optional templets as Laplacian templet, Canny templet, Sobel templet, Roberts templet and so on; step 3. calculating an initial clustering center and the functional value of an initial optimum value; step 4. determining a search point set and initializing pheromone concentration and relevant parameters according to the intial clustering center; step 5. arranging M ants at random positions, clustering each ant at the search point set and updating the overall optimum value; step 6. updating the pheromone concentration; step 7. repeating step 5 and step 6 until the predetermined algorithm is completed NCmax times; step 8. finishing the algorithm and outputting the optimal results. The multi-templet image separation method effectively improve the separation speed and the zone integrality, which is an efficient path for solving the problem of image separation.

Description

(1) Technical field [0001] The invention relates to a multi-template image segmentation method based on ant colony clustering (Ant Colony Clustering), which belongs to the field of computer vision information processing. (2) Background technology [0002] Image segmentation is an important issue in the field of image processing, and it is the basis of many image processing problems. It has been widely used in many fields, including image fusion, pattern recognition, computer vision, aircraft navigation, virtual reality, industrial inspection, traffic management, digital photogrammetry, medical image analysis, etc. However, due to the complexity of the picture background, the diversity of target features and the influence of noise, image segmentation has become a difficult point in image processing technology. [0003] As the most basic problem in the field of computer vision information processing, image segmentation has attracted many researchers in different fields, inclu...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T7/00G06N3/12
Inventor 段海滨罗松柏夏晓燕周国哲
Owner BEIHANG UNIV