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An Improved Image Segmentation Method Based on Graph and Color Texture Features

A technology of texture features and color features, applied in the fields of image processing and computer vision

Inactive Publication Date: 2017-02-08
NANJING UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to overcome the shortcomings of the traditional graph-based segmentation method using a single color feature for image segmentation resulting in serious mis-segmentation and over-segmentation, and to provide an improved image segmentation method based on graph and color texture features , the present invention obtains the unified coefficient of texture features and color features through multiple samples, effectively integrates the texture features and color features of pictures, uses the image segmentation method of the present invention to achieve high segmentation accuracy, and greatly reduces mis-segmentation phenomena

Method used

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  • An Improved Image Segmentation Method Based on Graph and Color Texture Features
  • An Improved Image Segmentation Method Based on Graph and Color Texture Features
  • An Improved Image Segmentation Method Based on Graph and Color Texture Features

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Embodiment 1

[0068] In conjunction with the accompanying drawings, an improved image segmentation method based on graph and color texture features of this embodiment, the specific flow chart is as follows Figure 4 As shown, the steps are as follows:

[0069] 1) Select 30 sample pictures, extract the texture features and color features of the 30 sample pictures, form a matrix Feature with the obtained texture features and color features, and calculate the covariance of the matrix Feature, and use the covariance as 30 samples The unified coefficient Σ of the color information and texture information of the picture.

[0070] Due to the difference in the statistical distribution of the texture information of the picture and the Lab color information, such as figure 2 As shown, among them, figure 2 (a) is the statistical histogram of all pixels in the 30 sample pictures according to the different Lab values. figure 2 (b) is the statistical histogram of the gray value of the texture image...

Embodiment 2

[0147] An improved image segmentation method based on graph and color texture features in this embodiment, the basic steps and segmentation effect are the same as those in Embodiment 1, the difference lies in: the value range of the initial threshold k when the combination criterion 1 is executed in step 5). is 450; the initial merging threshold k when implementing merging criterion 2 2 for 175.

Embodiment 3

[0149] An improved image segmentation method based on graph and color texture features in this embodiment, the basic steps and segmentation effect are the same as those in Embodiment 1, the difference lies in: the value range of the initial threshold k when the combination criterion 1 is executed in step 5). is 500; the initial merging threshold k when implementing merging criterion 2 2 for 200.

[0150] An improved image segmentation method based on graph and color texture features in the above embodiment has high segmentation accuracy and greatly reduces mis-segmentation and over-segmentation. It can provide stable segmentation results for post-applications such as content-based video retrieval, image retrieval, video codec, and motion estimation, and abstract useful object information.

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Abstract

The invention discloses an improved image segmentation method based on picture and color texture features, and relates to the technical fields of image processing and computer vision. The method comprises the following steps: (1) extracting the texture features and color features of 30 sample pictures, constructing a matrix by using the obtained texture features and color features, and solving the covariance of the matrix for serving as a unified coefficient of color information and texture information of the 30 sample pictures; (2) constructing a weighted undirected graph of a picture to be segmented; (3) extracting the texture feature and color feature of the picture to be segmented, and constructing a texture color feature descriptor of the picture to be segmented; (4) calculating the weights of sides in the weighted undirected graph of the picture to be segmented by using the uniform coefficient obtained in the step (1) and the texture color feature descriptor of the picture to be segmented obtained in the step (3); (5) merging and classifying nodes in the weighted undirected graph constructed in the step (2). The method has the advantages of high segmentation accuracy and little wrong segmentation and over-segmentation phenomena.

Description

technical field [0001] The invention belongs to the technical field of image processing and computer vision, and more specifically relates to an improved image segmentation method based on graph and color texture features. Background technique [0002] Image segmentation is an extremely important analysis method in computer vision and pattern recognition. The purpose of image segmentation is to divide the image into several different, non-overlapping regions with unique properties, extract the objects of interest, and add a unique class label to each pixel. Image segmentation is an important part of image analysis, and has been widely used in medical imaging, face recognition, fingerprint recognition, traffic control systems and machine vision. [0003] Color information and texture information are closely related to human perception, and segmentation methods based solely on texture or color cannot accurately describe the content of an image. Therefore, the research trend ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/40
Inventor 李勃王云烨陈惠娟陈抒瑢杨娴廖娟史德飞陈启美
Owner NANJING UNIV
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