Superpixel segmentation method based on fuzzy theory

A technology of superpixel segmentation and fuzzy theory, applied in the field of superpixel segmentation based on fuzzy theory, which can solve the problems of poor superpixel compactness, unfavorable image processing, and unsatisfactory effects.

Active Publication Date: 2013-10-16
山东幻科信息科技股份有限公司
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AI Technical Summary

Problems solved by technology

The superpixels generated by the Quick-shift algorithm are not fixed in shape and quantity, and the compactness of the superpixels is also poor.
The most important point is that the current main superpixel segmentation methods are all aimed at

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  • Superpixel segmentation method based on fuzzy theory
  • Superpixel segmentation method based on fuzzy theory

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Embodiment Construction

[0036] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0037] figure 1 Among them, the present invention is divided into seven steps: 1, initialize the clustering center; 2, the design of objective function; 3, update the degree of membership matrix; 4, update the clustering center, including gray value and coordinate; 5, repeat 3- Step 4, until the termination condition is satisfied; 6. Complete the preliminary superpixel division according to the finally obtained membership degree matrix; 7. Post-processing, complete the final superpixel division.

[0038] The specific process is as follows:

[0039] 1. Initialization

[0040]First, the image is processed into a regular grid according to the number of superpixel blocks to be divided, and the center point of each grid is selected as the initial clustering center. In order to avoid noise interference, a random disturbance is made here, that is, the initia...

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Abstract

The invention relates to a superpixel segmentation method based on the fuzzy theory. The superpixel segmentation method improves fitness of superpixel edges and original image edges, and segmented superpixels have an undiversified internal structure and uniform gray scale. The superpixel segmentation method comprises steps of 1) processing images and initializing cluster centers; 2) adding coordinate distances of pixel points into the fuzzy C-means clustering algorithm and establishing an objective function; 3) updating a membership matrix; 4) updating cluster centers with gray scale values and coordinates included; 5) repeating steps 3) and 4) until a termination condition that the change amount of the cluster center gray scale values is smaller than an artificially set threshold value or iteration times are larger than some artificially set value; 6) completing initial superpixel division based on the finally obtained membership matrix; and 7) performing post-processing to complete the final superpixel division by combining sets of points ,which are isolated and unavoidably exist in superpixels generated after the above six steps, with adjacent superpixels which have the maximum similarity.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a superpixel segmentation method based on fuzzy theory. Background technique [0002] The so-called superpixel is to use a certain algorithm to aggregate certain pixel points together to form an atomic region with a certain perceptual meaning, which is used to replace the previous hard-segmented regional grid. Superpixels can effectively utilize spatial constraint information, have a certain degree of noise resistance, and retain the original boundary information of the image while strengthening the local consistency of the image. The atomic region segmented by the superpixel also contains some Image features, such as shape, boundary contour information, and regional grayscale histogram, are beneficial to improve the accuracy of image processing, and in terms of time complexity, superpixels are also greatly improved compared to single pixel processing. In addition, for the uneven...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 尹义龙杨公平于振张擎张彩明
Owner 山东幻科信息科技股份有限公司
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