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Shape analysis and recognition based on skeleton and morphological structure
University of Newcastle, NSW 2308, Australia.
University of Newcastle, NSW 2308, Australia.
University of Newcastle, NSW 2308, Australia.
University of Technology Hawthorn, VIC3122, Australia.
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2010 (English)In: 5th European Conference onColour in Graphics, Imaging, and Vision12th International Symposium onMultispectral Colour Science, 2010, 118-123 p.Conference paper (Refereed)Text
Abstract [en]

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.

Place, publisher, year, edition, pages
2010. 118-123 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-127883DOI: 10.1109/CGIV.2010.26ISBN: 978-1-4244-7840-8OAI: oai:DiVA.org:liu-127883DiVA: diva2:930661
Conference
CGIV 2010/MCS’10. 7-10 Augusti 2010, Sydney, NSW
Available from: 2016-05-25 Created: 2016-05-13 Last updated: 2016-06-10

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Pham, Tuan D
Computer Vision and Robotics (Autonomous Systems)

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