Unsupervised texture classification: Automatically discover and classify   texture patterns

doi:10.1016/j.imavis.2007.08.003

CORC > 北京大学 > 信息科学技术学院

	Unsupervised texture classification: Automatically discover and classify texture patterns
	Qin, Lei ; Zheng, Qingfang ; Jiang, Shuqiang ; Huang, Qingining ; Gao, Wen
刊名	图像与视觉计算
	2008
关键词	unsupervised texture classification NMF PLSI invariant descriptor NONNEGATIVE MATRIX FACTORIZATION RETRIEVAL
DOI	10.1016/j.imavis.2007.08.003
英文摘要	In this paper, we present a novel approach to classify texture collections. This approach does not require experts to provide annotated training set. Given the image collection, we extract a set of invariant descriptors from each image. The descriptors of all images are veetor-quantized to form 'keypoints'. Then we represent the texture images by 'bag-of-keypoints' vectors. By analogy text classification, we use Probabilistic Latent Semantic Indexing (PLSI) and Non-negative Matrix Factorization (NMF) to perform unsupervised classification. The proposed approach is evaluated using the UIUC database which contains significant viewpoint and scale changes. We also report the results for simultaneously classifying I I I texture categories using the Brodatz database. The performances of classifying new images using the parameters learnt from the unannotated image collection are also presented. The experiment results clearly demonstrate that the approach is robust to scale and viewpoint changes, and achieves good classification accuracy even without annotated training set. (C) 2007 Elsevier B.V. All rights reserved.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000254686900005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Artificial Intelligence; Computer Science, Software Engineering; Computer Science, Theory & Methods; Engineering, Electrical & Electronic; Optics; SCI(E); EI; 2; ARTICLE; 5; 647-656; 26
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/249055]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Qin, Lei,Zheng, Qingfang,Jiang, Shuqiang,et al. Unsupervised texture classification: Automatically discover and classify texture patterns[J]. 图像与视觉计算,2008.
APA	Qin, Lei,Zheng, Qingfang,Jiang, Shuqiang,Huang, Qingining,&Gao, Wen.(2008).Unsupervised texture classification: Automatically discover and classify texture patterns.图像与视觉计算.
MLA	Qin, Lei,et al."Unsupervised texture classification: Automatically discover and classify texture patterns".图像与视觉计算 (2008).