Logo image clustering based on advanced statistics

Yi Wei; Mohamed Kamel; Yiwei He

doi:10.1117/12.750476

15 November 2007 Logo image clustering based on advanced statistics

Yi Wei, Mohamed Kamel, Yiwei He

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 67881Y (2007) https://doi.org/10.1117/12.750476
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Yi Wei, Mohamed Kamel, and Yiwei He "Logo image clustering based on advanced statistics", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67881Y (15 November 2007); https://doi.org/10.1117/12.750476

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