Unsupervised texture classification: automatically discover and classify texture patterns
文献类型：期刊论文
| 作者 | Qin, Lei1,2; Zheng, Qingfang1; Jiang, Shuqiang1; Huang, Qingining1,2; Gao, Wen1,3 |
| 刊名 | Image and vision computing
 |
| 出版日期 | 2008-05-01 |
| 卷号 | 26期号:5页码:647-656 |
| 关键词 | Unsupervised texture classification Nmf Plsi Invariant descriptor |
| ISSN号 | 0262-8856 |
| DOI | 10.1016/j.imavis.2007.08.003 |
| 通讯作者 | Qin, lei(lqin@jdl.ac.cn) |
| 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. |
| WOS关键词 | NONNEGATIVE MATRIX FACTORIZATION ; RETRIEVAL |
| WOS研究方向 | Computer Science ; Engineering ; Optics |
| WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Optics |
| 语种 | 英语 |
| WOS记录号 | WOS:000254686900005 |
| 出版者 | ELSEVIER SCIENCE BV |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2388192 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Qin, Lei |
| 作者单位 | 1.Chinese Acad Sci, Inst Computing Technol, Beijing, Peoples R China 2.Chinese Acad Sci, Grad Sch, Beijing, Peoples R China 3.Peking Univ, Sch Elect Engn & Comp Sci, Beijing, Peoples R China |
| 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]. Image and vision computing,2008,26(5):647-656. |
| APA | Qin, Lei,Zheng, Qingfang,Jiang, Shuqiang,Huang, Qingining,&Gao, Wen.(2008).Unsupervised texture classification: automatically discover and classify texture patterns.Image and vision computing,26(5),647-656. |
| MLA | Qin, Lei,et al."Unsupervised texture classification: automatically discover and classify texture patterns".Image and vision computing 26.5(2008):647-656. |
入库方式： iSwitch采集
来源：中国科学院大学
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。