Name
Title | ||
|---|---|---|
Extraction of Shell Texture Feature of Coscinodiscus for Classification Based on Wavelet and PCA |
Abstract | ||
|---|---|---|
Based on wavelet and principal component analysis(PCA), an effective shell texture feature of the coscinodiscus extraction method for classification is proposed in this paper.The feature extraction process involves a normalization of the given image with different sizes followed by shift invariant wavelet transform. The shift invariant feature is computed for subband of wavelet coefficients by PCA. The rate of recognition is calculated in the end. The experiments have proved the method is effective. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/JCAI.2009.75 | JCAI |
Keywords | Field | DocType |
normalization,image classification,wavelet transform | Normalization (statistics),Pattern recognition,Computer science,Image texture,Feature extraction,Artificial intelligence,Contextual image classification,Stationary wavelet transform,Principal component analysis,Wavelet transform,Wavelet | Conference |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li-Na Song | 1 | 0 | 0.34 |
| Guangrong Ji | 2 | 48 | 9.54 |
| Jing Chen | 3 | 111 | 13.60 |