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Method for performing texture segmentation on image and device thereof

An image segmentation and texture segmentation technology, which is applied in image analysis, image data processing, image enhancement and other directions, and can solve problems such as large amount of calculation of multiple gray levels and inability to adapt to multiple directions.

Inactive Publication Date: 2015-01-14
HITACHI LTD
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Problems solved by technology

[0005] In order to solve the above problems, the present invention provides an image segmentation method and device, which can solve the problems of being unable to adapt to multi-directions, multi-gray levels and large amount of calculation

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  • Method for performing texture segmentation on image and device thereof
  • Method for performing texture segmentation on image and device thereof
  • Method for performing texture segmentation on image and device thereof

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Embodiment Construction

[0073] The present invention will be described in detail below in conjunction with the embodiments.

[0074] In this example, the IKNOS multispectral image is used as the data source, with a resolution of 1m, to obtain such as figure 1 As shown in the image, the image has 512×512 pixels, and the image can be a color map. The image has multiple textures, in this case, for example, two textures of desert texture and artifact texture in the region.

[0075] refer to figure 2 , the method for image texture segmentation of the present invention comprises the following steps:

[0076] In step S0, the image is acquired, and in step S1, the image is converted into a grayscale image.

[0077] Next, in step S2, according to the size of the largest texture unit in the image, the grayscale image is divided into multiple regions of the same size, and multiple gradient feature vectors corresponding to the multiple regions are extracted. Wherein, the size of each of the multiple regions...

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Abstract

The invention provides a method for performing texture segmentation on an image, wherein the image is provided with a plurality of kinds of textures. The method comprises the following steps: converting the image to a grayscale image; according to the size of a largest texture unit in the image, dividing the grayscale image to a plurality of areas with same size, and extracting a plurality of gradient characteristic vectors which are in one-to-one correspondence with the plurality of areas; and performing fuzzy cluster analysis on the plurality of extracted gradient characteristic vectors, and classifying the plurality of areas, thereby classifying the parts with same pattern in the image into a same kind. The invention further provides a device for performing texture segmentation on the image. The method and the device for performing texture segmentation on the image according to the invention can be adapted for multiple directions and multiple gray scales and furthermore have small computing amount.

Description

technical field [0001] The present invention relates to a method and device for image segmentation, in particular to a method and device for image texture segmentation. Background technique [0002] With the development of information technology, images are increasingly used to obtain and analyze various information. Image segmentation in the field of image processing has also become the focus of research. [0003] At present, image segmentation methods are mainly divided into two categories: color segmentation and texture segmentation. Since the texture information is richer than the color feature information, the significance of texture segmentation is more important. Texture segmentation currently mainly includes texture segmentation methods based on gray level co-occurrence matrix and wavelet analysis. "Bamboo forest information extraction from IKONOS images based on gray level co-occurrence matrix" mainly divides the image into multiple small areas, extracts the gray...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T7/42G06T2207/20112
Inventor 张岱张学
Owner HITACHI LTD
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