Image segmentation method by using nucleus transmission

An image segmentation and kernel transfer technology, applied in the field of image processing, can solve the problems of reducing segmentation accuracy, only considering local characteristics, losing global optimization characteristics, etc., to achieve the effect of maintaining consistency, improving segmentation accuracy, and improving computational efficiency

Inactive Publication Date: 2011-11-23
XIDIAN UNIV
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Problems solved by technology

Although these methods improve the computational efficiency, there are still some problems: 1) the consistency between superpixel data points cannot be maintained; 2) the Gaussian similarity function is used to calculate the similarity betwe...

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  • Image segmentation method by using nucleus transmission
  • Image segmentation method by using nucleus transmission
  • Image segmentation method by using nucleus transmission

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Embodiment Construction

[0023] refer to figure 1 , the implementation steps of the present invention include as follows:

[0024] Step 1, extract the color features of the input image

[0025] Input an image, extract the color features of the image in the Luv color space, and the color features of all pixels form a matrix F={f with a size of num_pixel*3 L , f u , f v}, each row represents the color feature of a pixel, num_pixel represents the number of pixels of the image, f L , f u , f v Respectively represent the characteristics of the luminance component L, the chromaticity coordinate component u and the chromaticity coordinate component v of the Luv color space.

[0026] Step 2, pre-segment the input image to get the superpixel set

[0027] (2.1) Use the mean shift method to pre-segment the input image to obtain the label of each pixel, the label ranges from 1 to n, find the pixels with the same label, and merge the pixels with the same label into one area, and give each A label s for ove...

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Abstract

The invention discloses an image segmentation method by using nucleus transmission to solve problems of large storage scale and data inconsistency in a present method. The method comprises the following steps: inputting an image, extracting color characteristics of the image, obtaining a super-pixel set of the input image by using a mean value shift method, and calculating a super-pixel color characteristic set; searching a seed point set in the super-pixel color characteristic set by using a k-means clustering method; updating a label of the seed point set by using an adaptive spectral clustering method and forming a constraint set; sending constraint information in the constraint set to whole super-pixel color feature set space by using a nucleus transmission method and obtaining a nucleus matrix; clustering the nucleus matrix by using a k- means method to obtain label vector of the super-pixel, and outputting a segmentation result. The method in the invention has the characteristics of low storage scale, maintenance of data consistency, high calculating efficiency and high segmentation precision, and can be used for object detection and tracking, medical image analysis, network image retrieval and conference video monitoring.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to an image segmentation method, in particular to an image segmentation method using kernel transfer, which can be used for target detection and tracking, medical image analysis, network image retrieval and conference video monitoring. Background technique [0002] Digital image processing technology is an interdisciplinary field. With the continuous development of computer science and technology, image processing and analysis have gradually formed an independent scientific system. Image segmentation is an important image processing technology that can be applied to medical image detection of lesion areas, target recognition and tracking, network image retrieval, video surveillance etc. Image segmentation is a key step in image processing. It can be said that the quality of image segmentation results directly affects the understanding of images. [0003] There are many methods and ty...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 郑喆坤焦李成刘娟沈彦波侯彪王爽尚荣华马文萍公茂果
Owner XIDIAN UNIV
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