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Proceedings Paper

Logo image clustering based on advanced statistics
Author(s): Yi Wei; Mohamed Kamel; Yiwei He
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Paper Abstract

In recent years, there has been a growing interest in the research of image content description techniques. Among those, image clustering is one of the most frequently discussed topics. Similar to image recognition, image clustering is also a high-level representation technique. However it focuses on the coarse categorization rather than the accurate recognition. Based on wavelet transform (WT) and advanced statistics, the authors propose a novel approach that divides various shaped logo images into groups according to the external boundary of each logo image. Experimental results show that the presented method is accurate, fast and insensitive to defects.

Paper Details

Date Published: 15 November 2007
PDF: 6 pages
Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67881Y (15 November 2007); doi: 10.1117/12.750476
Show Author Affiliations
Yi Wei, Wuhan Univ. of Technology (China)
Mohamed Kamel, Univ. of Waterloo (Canada)
Yiwei He, Wuhan Univ. of Technology (China)

Published in SPIE Proceedings Vol. 6788:
MIPPR 2007: Pattern Recognition and Computer Vision
S. J. Maybank; Mingyue Ding; F. Wahl; Yaoting Zhu, Editor(s)

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