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Shape analysis and recognition based on skeleton and morphological structure

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conference contribution
posted on 2025-05-08, 12:51 authored by Donggang Yu, Jesse S. Jin, Suhuai LuoSuhuai Luo, Wei Lai, Mira Park, Tuan D. Pham
This paper presents a novel and effective method of shape analysis and recognition based on skeleton and morphological structure. A series of preprocessing algorithms, smooth following and liberalization are introduced, and series of morphological structural points of image contour are extracted and merged. A series of basic shapes and a main shape of object image are described and segmented based on skeleton and morphological structure. Object shape is efficiently analyzed and recognized based on the extracted series of basic shapes and main shape. Comparing with other methods, the proposed method need not sample training set. Also, the new method can be used to analyze and recognize the shape structure of any shape, and there is no any requirement for the processed image data set. The new method can be used in image analysis, intelligent recognition, techniques, applications, systems and tools.

History

Source title

Proceedings: 2010 Seventh International Conference on Computer Graphics, Imaging and Visualization

Name of conference

7th International Conference on Computer Graphics, Imaging and Visualization (CGIV 2010)

Location

Sydney

Start date

2010-08-07

End date

2010-08-10

Pagination

118-123

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Place published

Los Alamitos, CA

Language

  • en, English

College/Research Centre

Faculty of Science and Information Technology

School

School of Design, Communication and Information Technology

Rights statement

Copyright © 2010 IEEE. Reprinted from Proceedings: 2010 Seventh International Conference on Computer Graphics, Imaging and Visualization. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

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