Name
Abstract | ||
|---|---|---|
In this paper, we propose a new descriptor of texture images based on the characterization of the spatial patterns of image key-points. Regarding the set of visual keypoints of a given texture sample as the realization of marked point process, we define texture features from multivariate spatial statistics. Our approach initially relies on the construction of a codebook of the visual signatures of the keypoints. Here these visual signatures are given by SIFT feature vectors and the codebooks are issued from a hierarchical clustering algorithm suitable for processing large high-dimensional dataset. The texture descriptor is formed by cooccurrence statistics of neighboring keypoint pairs for different neighborhood radii. The proposed descriptor inherits the invariance properties of the SIFT w.r.t. contrast change and geometric image transformation (rotation, scaling). An application to texture recognition using the discriminative classifiers, namely: k-NN, SVM and random forest, is considered and a quantitative evaluation is reported for two case-studies: UIUC texture database and real sonar textures. The proposed approach favourably compares to previous work. We further discuss the properties of the proposed descriptor, including dimensionality aspects. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15561-1_55 | ECCV (4) |
Keywords | Field | DocType |
spatial statistic,proposed descriptor,new descriptor,visual signature,texture recognition,texture image,visual keypoints,texture descriptor,real sonar texture,uiuc texture database,texture feature,texture sample,spatial statistics,spatial pattern,hierarchical clustering,random forest,feature vector | Spatial analysis,Scale-invariant feature transform,Computer science,Artificial intelligence,Hierarchical clustering,Computer vision,Feature vector,Texture Descriptor,Pattern recognition,Image texture,Machine learning,Texture filtering,Visual Word | Conference |
Volume | ISSN | ISBN |
6314 | 0302-9743 | 3-642-15560-X |
Citations | PageRank | References |
5 | 0.49 | 19 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huu-Giao Nguyen | 1 | 21 | 3.14 |
| Ronan Fablet | 2 | 312 | 47.04 |
| Jean-Marc Boucher | 3 | 132 | 22.28 |