Image indexing method based on clustering via Info-Kmeans under pair constraints
Constructing high-quality content-based image indexing is fairly difficult due to the large amount of noise in the data set and the high-dimension and the sparseness of the image data.To meet this challenge,a novel noise-filtering and clustering was proposed using Info-Kmeans based image indexing co...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2013-07-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.07.018/ |
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| Summary: | Constructing high-quality content-based image indexing is fairly difficult due to the large amount of noise in the data set and the high-dimension and the sparseness of the image data.To meet this challenge,a novel noise-filtering and clustering was proposed using Info-Kmeans based image indexing construction method. Firstly,a noise-filtering me-thod using the cosine interesting patterns was presented. Secondly,a novel Info-Kmeans algorithm was proposed which could avoid the zero-feature dilemma caused by the use of KL-divergence and exploit the prior knowledge in the form of pair constraints. The experimental results on the two image data sets,LFW and Oxford_5K,well demonstrate that: noise filter can improve the clustering performance remarkably and the novel Info-Kmeans algorithm yields better results than the existing clustering tool. |
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| ISSN: | 1000-436X |