15 November 2007 Novel color image segmentation using self-generating prototypes
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Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67864A (2007) https://doi.org/10.1117/12.751169
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
A new self-generating prototypes method based on SGNT is presented. This method uses reference patterns as initial prototype. This procedure can be implemented in a SGNT with specific architecture consisting of one root and the initial class number of reference patterns. The leaf in SGNT is defined with prototype vector, learning vector, center property vector and distant property vector. After training, prototype set are outputted. The main advantage of this method is that both the number of prototypes and their locations are learned from the training set without much human intervention. Experiments with synthesis and real color image the excellent performance of this classification scheme as compared to existing K-nearest neighbor (K-NN) and Learning vector quantization (LVQ) algorithm.
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Chunping Liu, Chunping Liu, Xiaohua Yuan, Xiaohua Yuan, Zhaohui Wang, Zhaohui Wang, } "Novel color image segmentation using self-generating prototypes", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67864A (15 November 2007); doi: 10.1117/12.751169; https://doi.org/10.1117/12.751169
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