標題: Texture recognition by generalized probabilistic decision-based neural networks
作者: Xu, Yeong-Yuh
Tseng, C. -L.
Fu, Hsin-Chia
資訊工程學系
Department of Computer Science
關鍵字: Bayesian decision-based neural networks;Generalized probabilistic decision-based neural networks;GPDNN;Texture recognition;Supervised learning
公開日期: 1-五月-2011
摘要: Texture recognition have received tremendous attentions in the past decades, due to its wide applications in computer vision and pattern recognition. For various applications, formulating texture features in distributional forms can sometimes provide meaningful representation than in numerical forms. In this paper, a generalized probabilistic decision-based neural network (GPDNN), based on a novel methodology for the measurement of the difference between two distributions, is proposed for texture recognition. Based on a two-layer pyramid-type network structure, the proposed GPDNN receives texture data via 2-D grid input nodes, and outputs the classification and/or retrieval results at the top layer node. Our prototype system demonstrates a successful utilization of GPDNN to the texture recognition on 40 texture images selected from the MIT Vision Texture (VisTex) database. Regarding the performance, experiment results show that (1) based on the proposed distribution difference measurement method, the texture retrieval accuracy is improved from 77% to 82% by comparing with some recently published leading methods, and (2) the proposed GPDNN has significant improvements in classification accuracy from 82.2% to 90.1% and retrieval accuracy from 79.9% to 88.6% by comparing with traditional approaches. (C) 2010 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.eswa.2010.11.051
http://hdl.handle.net/11536/8980
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2010.11.051
期刊: EXPERT SYSTEMS WITH APPLICATIONS
Volume: 38
Issue: 5
起始頁: 6184
結束頁: 6189
顯示於類別:期刊論文


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