Name
Title | ||
|---|---|---|
An approach to texture segmentation analysis based on sparse coding model and EM algorithm |
Abstract | ||
|---|---|---|
Sparse coding theory is a method for finding a reduced representation of multidimensional data When applied to images, this theory can adopt efficient codes for images that captures the statistically significant structure intrinsic in the images In this paper, we mainly discuss about its application in the area of texture images analysis by means of Independent Component Analysis Texture model construction, feature extraction and further segmentation approaches are proposed respectively The experimental results demonstrate that the segmentation based on sparse coding theory gets promising performance. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-13318-3_17 | ISNN (2) |
Keywords | Field | DocType |
segmentation approach,sparse coding theory,independent component analysis texture,promising performance,feature extraction,multidimensional data,texture segmentation analysis,sparse coding model,texture images analysis,em algorithm,model construction,efficient code,statistical significance,sparse coding,image analysis,independent component analysis | Scale-space segmentation,Computer science,Artificial intelligence,Computer vision,Pattern recognition,Neural coding,Image texture,Expectation–maximization algorithm,Segmentation,Sparse approximation,Feature extraction,Independent component analysis,Machine learning | Conference |
Volume | ISSN | ISBN |
6064 | 0302-9743 | 3-642-13317-7 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lijuan Duan | 1 | 215 | 26.13 |
| Jicai Ma | 2 | 1 | 0.69 |
| Zhen Yang | 3 | 23 | 3.88 |
| Jun Miao | 4 | 220 | 22.17 |