Name
Abstract | ||
|---|---|---|
This Letter presents a new feature named structured local binary Kirsch pattern (SLBKP) for image retrieval. Each input color image is decomposed into Y, Cb and Cr components. For each component image, eight 3 x 3 Kirsch direction templates are first performed pixel by pixel, and thus each pixel is characterized by an 8-dimenional edge-strength vector. Then a binary operation is performed on each edge-strength vector to obtain its integer-valued SLBKP. Finally, three SLBKP histograms are concatenated together as the final feature of each input colour image. Experimental results show that, compared with the existing structured local binary Haar pattern (SLBHP)-based feature, the proposed feature can greatly improve retrieval performance. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1587/transinf.E96.D.1230 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
image retrieval, structured local binary Haar pattern, structured local binary Kirsch pattern | Computer vision,Pattern recognition,Computer science,Image retrieval,Artificial intelligence,Binary number | Journal |
Volume | Issue | ISSN |
E96D | 5 | 0916-8532 |
Citations | PageRank | References |
4 | 0.41 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guangyu Kang | 1 | 7 | 1.91 |
| Shize Guo | 2 | 145 | 23.21 |
| De-Chen Wang | 3 | 4 | 0.41 |
| Long-hua Ma | 4 | 132 | 17.89 |
| Lu Zhe-Ming | 5 | 635 | 72.85 |