Name
Abstract | ||
|---|---|---|
In this paper, we propose an image retrieval system that uses both local and global shape features to retrieve the most similar images from the database. To obtain both features, some pre-processing steps, such as object segmentation using Minimum Error Thresholding and border extraction, are firstly carried out. After that, the Grid Based method is used to extract the global shape feature. The system divides the image into smaller areas and extracts local features by applying discrete wavelet transform and singular value decomposition. Finally, we compute the similarities between the global and local features of the query image and all the images in the database to give the most possible candidate matches as a result. The experimental results show the strengths and effectiveness of the proposed system. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2448556.2448648 | ICUIMC |
Keywords | Field | DocType |
discrete wavelet,query image,similar image,minimum error thresholding,shape decomposition,extracts local feature,proposed system,border extraction,global shape feature,local feature,image retrieval system,wavelet transform,information retrieval | Top-hat transform,Computer vision,Automatic image annotation,Pattern recognition,Computer science,Image retrieval,Artificial intelligence,Stationary wavelet transform,Wavelet packet decomposition,Content-based image retrieval,Visual Word,Wavelet transform | Conference |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Do Yen | 1 | 0 | 1.01 |
| Soo Hyung Kim | 2 | 29 | 6.39 |
| In Seop Na | 3 | 42 | 13.83 |
| Dae Wook Kang | 4 | 1 | 0.70 |
| Jin Hyung Kim | 5 | 472 | 37.29 |