Name
Title | ||
|---|---|---|
Texture Classification by using Advanced Local Binary Patterns and Spatial Distribution of Dominant Patterns |
Abstract | ||
|---|---|---|
In this paper, we propose a new feature extraction method, which is robust against rotation and histogram equalization for texture classification. To this end, we introduce the concept of advanced local binary patterns (ALBP), which reflects the local dominant structural characteristics of different kinds of textures. In addition, to extract the global spatial distribution feature of the ALBP patterns, we incooperate ALBP with the aura matrix measure as the second layer to analyze texture images. The proposed method has three novel contributions, (a) The proposed ALBP approach captures the most essential local structure characteristics of texture images (i.e. edges, corners); (b) the proposed method extracts global information by using Aura matrix measure based on the spatial distribution information of the dominant patterns produced by ALBP; and (c) the proposed method is robust to rotation and histogram equalization. The proposed approach has been compared with other widely used texture classification techniques and evaluated by applying classification tests to randomly rotated and histogram equalized images in two different texture databases: Brodatz and CUReT. The experimental results show that the classification accuracy of the proposed method exceeds the ones obtained by other image features. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICASSP.2007.366134 | ICASSP (1) |
Keywords | Field | DocType |
spatial distribution information,spatial distribution,advanced local binary patterns,aura matrix,texture classification,matrix algebra,texture databases,feature extraction method,feature extraction,image classification,image texture,index terms— texture classification,histogram equalization,robustness,image analysis,data mining,local binary pattern,indexing terms,image features,pattern analysis,histograms,testing | Histogram,Computer vision,Pattern recognition,Computer science,Image texture,Feature (computer vision),Local binary patterns,Robustness (computer science),Feature extraction,Artificial intelligence,Contextual image classification,Histogram equalization | Conference |
Volume | ISSN | ISBN |
1 | 1520-6149 | 1-4244-0727-3 |
Citations | PageRank | References |
18 | 0.96 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shu Liao | 1 | 128 | 7.88 |
| Albert C. S. Chung | 2 | 964 | 72.07 |