Name
Abstract | ||
|---|---|---|
We address the problem of retrieving images from a large database using an image as a query. The method is specifically aimed at databases that store images in JPEG format, and works in the compressed domain to create index keys. A key is generated for each image in the database and is matched with the key generated for the query image. The keys are independent of the size of the image. Images that have similar keys are assumed to be similar, but there is no semantic meaning to the similarity. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1109/34.531805 | IEEE Trans. Pattern Anal. Mach. Intell. |
Keywords | Field | DocType |
semantic meaning,large database,store image,retrieving image,jpeg format,query image,similar key,index key,jpeg compression scheme,image retrieval,indexes,jpeg,dct,indexation,information retrieval,transform coding,layout,data compression | Computer vision,Automatic image annotation,Pattern recognition,Computer science,Image processing,Image retrieval,Digital image,JPEG File Interchange Format,JPEG,Artificial intelligence,Quantization (image processing),Image compression | Journal |
Volume | Issue | ISSN |
18 | 8 | 0162-8828 |
Citations | PageRank | References |
59 | 4.94 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Shneier | 1 | 257 | 52.18 |
| Mohamed Abdel-Mottaleb | 2 | 993 | 80.22 |
| Abdel-Mottaleb, M. | 3 | 59 | 4.94 |