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Rapid graph matching and recognition method based on skeleton graphs

A skeleton diagram and graphics technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of low matching efficiency, complex graphics without recognition effect, high time complexity, etc., and achieve the goal of reducing time complexity Effect

Active Publication Date: 2015-01-21
XIDIAN UNIV
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Problems solved by technology

However, this method cannot effectively use the features inside the shape outline, does not have a good recognition effect on complex graphics, and has high time complexity and low matching efficiency

Method used

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  • Rapid graph matching and recognition method based on skeleton graphs
  • Rapid graph matching and recognition method based on skeleton graphs
  • Rapid graph matching and recognition method based on skeleton graphs

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Embodiment Construction

[0038] The problem of pattern matching and recognition can be abstracted as the problem of extracting pattern eigenvectors and calculating the similarity of eigenvectors.

[0039] refer to figure 1 , the specific implementation steps of graphic matching and recognition based on the skeleton graph designed by the present invention are as follows:

[0040] Step 1: Input N images S of the graph dataset i , i=1,2,...,N, since the input image is a binary image, directly use the canny edge detection operator to extract the contour C of each image i , i=1,2,...,N. Among them, the canny detection operator was proposed by John Canny in 1986.

[0041] Step 2: Contour C of the graph i Perform clockwise uniform sampling to obtain M sampling points P at equal intervals ij (j=1,2,...,M):

[0042] (2a) Arrange the contour points on the graph clockwise from the lower left corner of the graph to form a one-dimensional vector C i ={c i1 ,c i2 ,...,c im}(m is the number of contour poin...

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Abstract

The invention belongs to the technical fields of pattern recognition and computer vision, and particularly discloses a rapid graph matching and recognition method based on skeleton graphs. The graph recognition accuracy is guaranteed, and meanwhile the graph matching speed is increased. The rapid graph matching and recognition method includes the implementation steps of (1) extracting outlines of graphs through a classic canny edge detection operator; (2) sampling the outlines of the graphs at equal intervals; (3) splitting the graphs with the sampling points as peaks of triangles; (4) building the internal skeleton structure graphs of the graphs; (5) extracting feature vectors of the skeleton graphs of the graphs; (6) calculating a matching cost matrix of the graphs; (7) finding optimal matching points of the graphs; (8) rotating the skeleton structure graphs of the graphs, and repeating the step (6) and the step (7); (9) outputting the minimum matching cost for serving as the similarity distance of the graphs. By means of the rapid graph matching and recognition method, under the condition that the certain recognition accuracy is maintained, the complexity of a shape descriptor operator is effectively lowered, and the graph matching speed is increased.

Description

technical field [0001] The invention belongs to the field of pattern recognition and computer vision, and relates to a pattern recognition method based on a pattern internal structure diagram, in particular to a skeleton diagram-based fast pattern matching and recognition method, which can be applied to fast pattern matching and recognition. Background technique [0002] In recent years, with the rapid development of science and technology and computer Internet technology, digital images are used more and more widely in all walks of life. In the digital ocean, how to quickly recognize an image has always been a hot topic of discussion in computer vision and pattern recognition. Since content-based image retrieval technology (content-based image retrieval) was proposed in the early 1990s, it has been a research hotspot for researchers. It mainly realizes image recognition and retrieval by extracting features such as image texture, color, target shape and their spatial positi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06K9/62
CPCG06V10/752
Inventor 刘若辰焦李成朱彬彬熊涛王爽马晶晶张向荣李阳阳
Owner XIDIAN UNIV
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