Name
Title | ||
|---|---|---|
A new K-View algorithm for texture image classification using rotation-invariant feature |
Abstract | ||
|---|---|---|
This paper proposes a new K-View algorithm for texture image classification using rotation-invariant features. These features are statistically derived from characteristic view sets for each texture. Unlike the existing K-View algorithm, all the views used are transformed into rotation-invariant features and the K views are selected randomly. In contrast, the existing K-View algorithm uses the K-means algorithm for choosing the K views. In this new algorithm the decision of determining a pixel to which texture class it belong to, is made by considering all the views which consist of the pixel being classified. In order to preserve the primitive information of a texture class as much as possible, the proposed algorithm randomly selects k views of the view set from each sample sub-image as the characteristic view set. Experimental results show that the proposed algorithm is more robust and accurate compared with the results of the existing K-View algorithm. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1529282.1529481 | SAC |
Keywords | Field | DocType |
characteristic view set,existing k-view algorithm,k view,texture class,texture image classification,new algorithm,k-means algorithm,new k-view algorithm,proposed algorithm,rotation-invariant feature,image classification,k means algorithm | Computer vision,Ramer–Douglas–Peucker algorithm,Invariant feature,Pattern recognition,Computer science,Algorithm,Pixel,Artificial intelligence,Contextual image classification | Conference |
Citations | PageRank | References |
4 | 0.59 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong Liu | 1 | 96 | 18.53 |
| Siguang Dai | 2 | 4 | 0.59 |
| Enmin Song | 3 | 176 | 24.53 |
| Cihui Yang | 4 | 4 | 0.59 |
| Chih-Cheng Hung | 5 | 4 | 0.59 |