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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gang Liu Gui-Song Xia Wen Yang Liangpei Zhang |
| Copyright Year | 2014 |
| Description | Author affiliation: Electron. Inf. Sch., Wuhan Univ., Wuhan, China (Wen Yang) || State Key Lab. LIESMARS, Wuhan Univ., Wuhan, China (Gang Liu; Gui-Song Xia; Liangpei Zhang) |
| Abstract | This paper presents a flexible shape-based texture analysis method by investigating the co-occurrence patterns of shapes. More precisely, a texture image is represented by a tree of shapes, each of which is associated with several attributes. The modeling of texture is thus converted to characterize the tree of shapes. To this aim, we first learn a set of co-occurrence patterns of shapes from texture images, then establish a bag-of-words model on the learned shape co-occurrence patterns (SCOPs), and finally use the resulting SCOPs distributions as features for texture analysis. In contrast with existing work, the proposed method not only inherits the strong ability to depict geometrical aspects of textures and the high robustness to variations of imaging conditions from the shape-based texture analysis method, but also provides a more flexible way to model shape relationships (high-order statistics) on the tree. To our knowledge, this is the first time to use co-occurrence patterns of explicit shapes as a tool for texture analysis. Experiments of texture retrieval and classification on various databases report state-of-the-art results and demonstrate the efficiency of the proposed method. |
| Starting Page | 1627 |
| Ending Page | 1632 |
| File Size | 1061935 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479952090 |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2014.288 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-24 |
| Publisher Place | Sweden |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Shape Databases Analytical models Level set Transforms Histograms Training |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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