| A novel visual codebook model based on fuzzy geometry for large-scale image classification | |
Li, Yanshan1; Huang, Qinghua2,3; Xie, Weixin1; Li, Xuelong4
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| 2015-10-01 | |
| 发表期刊 | PATTERN RECOGNITION
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| 卷号 | 48期号:10页码:3125-3134 |
| 摘要 | The codebook model has been developed as an effective means for image classification. However, the inherent operation of assigning visual words to image feature vectors in traditional codebook approaches causes serious ambiguities in image classification. In particular, the nearest word may not be the best fit to a feature, and multiple words may be equally appropriate for one specific feature. To resolve these ambiguities, we propose a novel visual codebook model based on the n-dimensional fuzzy geometry (n-D FG) theory, where all visual words and features are modeled as fuzzy points in the n-D FG space, and appropriate uncertainty is introduced to each fuzzy point to enhance the representation capacity. This n-D FG-codebook model not only inherits advantages from the fuzzy set theory, but also facilitates the analysis and determination of the relationship between visual words and features in geometric form. By explicitly taking into account the ambiguities, we propose a novel measure of similarity between the visual words and fuzzy features. Following the proposed codebook model and the novel similarity measure, we develop two useful image classification algorithms by modifying popular image coding algorithms (i.e. SPM and LLC). Finally, experimental results demonstrate that the classification accuracy of the proposed algorithms is dramatically improved for a standard large-scale image database. For example, with a codebook size of 256, the proposed algorithms achieve similar performance as traditional algorithms with a codebook size of 1024, indicating that the proposed algorithms reduce the computational cost by 75% while achieving almost identical classification accuracy to traditional algorithms. Thus, the proposed algorithms represent a more efficient and appropriate scheme for big image data. (C) 2015 Elsevier Ltd. All rights reserved. |
| 文章类型 | Article |
| 关键词 | Codebook Fuzzy Geometry Fuzzy Set Theory Image Classification |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1016/j.patcog.2015.02.010 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | SPARSE REPRESENTATION ; PLANE GEOMETRY ; RECOGNITION ; SEGMENTATION ; SET |
| 语种 | 英语 |
| WOS研究方向 | Computer Science ; Engineering |
| WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000357246100015 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/25145 |
| 专题 | 光谱成像技术研究室 |
| 作者单位 | 1.Shenzhen Univ, ATR Natl Key Lab Def Technol, Shenzhen 518060, Peoples R China 2.S China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510640, Guangdong, Peoples R China 3.Natl Engn Res Ctr Tissue Restorat & Reconstruct, Guangzhou, Guangdong, Peoples R China 4.Chinese Acad Sci, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Yanshan,Huang, Qinghua,Xie, Weixin,et al. A novel visual codebook model based on fuzzy geometry for large-scale image classification[J]. PATTERN RECOGNITION,2015,48(10):3125-3134. |
| APA | Li, Yanshan,Huang, Qinghua,Xie, Weixin,&Li, Xuelong.(2015).A novel visual codebook model based on fuzzy geometry for large-scale image classification.PATTERN RECOGNITION,48(10),3125-3134. |
| MLA | Li, Yanshan,et al."A novel visual codebook model based on fuzzy geometry for large-scale image classification".PATTERN RECOGNITION 48.10(2015):3125-3134. |
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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| A novel visual codeb（1140KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 | |
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