Texture image segmentation method based on Lamarck multi-target immune algorithm

A texture image and immune algorithm technology, applied in the field of image processing, can solve the problems of large amount of computing data, single evaluation index, insufficient local search ability, etc., and achieve the effect of good simulation experiment performance, low computational complexity, and superior segmentation effect

Active Publication Date: 2010-10-20
XIDIAN UNIV
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Problems solved by technology

[0009] In summary, the existing image segmentation methods based on cluster analysis have the following three problems: (1) the amount of computing data is too large; (2) the global optimization ability is not strong; (3) the evaluation index is single; (4) local search lack of ability
If the above problems...

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  • Texture image segmentation method based on Lamarck multi-target immune algorithm
  • Texture image segmentation method based on Lamarck multi-target immune algorithm
  • Texture image segmentation method based on Lamarck multi-target immune algorithm

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Embodiment Construction

[0047] refer to figure 1 , the segmentation steps of the present invention include as follows:

[0048] Step 1. Extract image information.

[0049] First, input the image to be segmented; second, select 4 discrete directions according to the gray co-occurrence matrix, which are 0°, 45°, 90° and 135°, and extract three quadratic statistics along each direction as texture features , which are the second-order moment of the angle, the homogeneous area and the correlation, and a total of 12-dimensional feature information; then, three-layer wavelet transform is used to extract the feature quantities of 10 sub-bands from the image to be segmented, and a total of 10-dimensional feature information; finally, the gray level co-occurrence matrix The 12-dimensional feature information and the 10-dimensional feature information of wavelet energy are merged together, and a total of 22-dimensional feature information is obtained.

[0050] Step 2. Generate a test sample set.

[0051] Aim...

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Abstract

The invention discloses a texture image segmentation method based on Lamarck multi-target immune algorithm, mainly aiming at solving the problems of high operational data quantity, weak global optimization capability, one-sided evaluation index and poorer local searching capability in the prior art. The texture image segmentation method comprises the steps of: (1) extracting image grey-scale information and image small wave energy information; (2) based on watershed pre-segmentation, generating a test sample set for image sampling; (3) using the Lamarck multi-target immune algorithm for carrying out data clustering on the test sample set, and generating a data clustering scheme sets (4) according to the Minkowski index value, selecting the most satisfied data clustering scheme; (5) according to the selected data clustering scheme, marking image pixel point category attribution; and (6) outputting the image segmentation result. The texture image segmentation method has the advantages of low operational data quantity, lower calculation complexity, high image segmentation average accuracy rate and excellent segmentation result, and can be used for image information acquisition and image texture partition.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to image segmentation, in particular to a texture image segmentation method based on a Lamarck multi-object immune algorithm, which can be used for image understanding and object recognition. Background technique [0002] After entering the 21st century, there are more and more image data, and machine interpretation has replaced human interpretation. Image processing is increasingly playing an important role related to the national economy and people's livelihood, and has become the focus of current scientific research. Image segmentation is one of the fundamental problems in image processing. Image engineering can usually be divided into three levels, image processing, image analysis and image understanding. As an important step in the process from image processing to image analysis, image segmentation is the basis for further image understanding. The task of image segment...

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Application Information

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IPC IPC(8): G06T7/00G06K9/62
Inventor 焦李成张伟刘若辰刘芳王爽公茂果李阳阳侯彪
Owner XIDIAN UNIV
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