Name
Abstract | ||
|---|---|---|
This paper presents a novel approach for coin image recognition. The approach enables measuring the similarity between full color multi-component coin images and needs no cost intensive image segmentation. A novel procedure, based on strong edges of the coin image, is exploited to derive an abstract image. Spiral decomposition of pixels in the abstract image is then used to extract a set of compact and effective features. The query set and the image database used in the tests are scanned, photographed, or collected from the web. The results are compared with three other well-known approaches within the literature. Experimental results show significant improvement in the Recall ratio using the proposed features. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ISSPA.2007.4555308 | Sharjah |
Keywords | Field | DocType |
image colour analysis,image recognition,image segmentation,abstract images,coin image recognition,coin recognition,full color multicomponent coin images,image abstraction,image segmentation,spiral decomposition | Histogram,Computer vision,Pattern recognition,Feature detection (computer vision),Computer science,Image texture,Image processing,Image segmentation,Feature extraction,Pixel,Artificial intelligence,Standard test image | Conference |
ISBN | Citations | PageRank |
978-1-4244-1779-8 | 1 | 0.38 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chalechale, A. | 1 | 1 | 0.38 |
| A. Chalechale | 2 | 1 | 0.38 |