Logo recognition based on membership degree and closeness degree of fuzzy sets Online publication date: Sat, 21-Mar-2015
by Gang Wang, Lizhu Liu, Yanqing Jin
International Journal of Modelling, Identification and Control (IJMIC), Vol. 12, No. 1/2, 2011
Abstract: Fuzzy information theory which is based on fuzzy theory is a departure from information science. Higher performance could be obtained in pattern recognition with fuzzy sets theory. People combine fuzzy sets theory with pattern recognition and established fuzzy pattern recognition. This paper presents our work in the field of logo recognition by using fuzzy sets theory. Aim at the application requirement of logo recognition in image intelligent processing, a logo recognition algorithm based on membership degree and closeness degree of fuzzy sets is proposed. By fuzzy mapping, the logo's gridding feature is transformed to the membership degree of fuzzy sets; then using closeness degree and closest principle of fuzzy sets to accomplish logo recognition. The algorithm significantly enhances the adaptability and anti-interference to poor quality images and effectively improves the flexible processing capability of logo recognition system. Experimental results show that the recognition rate of this logo recognition algorithm can reach as high as 94.5%.
Online publication date: Sat, 21-Mar-2015
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