Abstract
A comprehensive survey on patch recognition, which is a crucial part of content-based image retrieval (CBIR), is presented. CBIR can be viewed as a methodology in which three correlated modules including patch sampling, characterizing, and recognizing are employed. This paper aims to evaluate meaningful models for one of the most challenging problems in image understanding, specifically, for the effective and efficient mapping between image visual features and high-level semantic concepts. To achieve this, the latest classification, clustering, and interactive methods have been meticulously discussed. Finally, several recommendations for future research issues have been suggested based on the weaknesses of recent technologies.
| Original language | English |
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| Title of host publication | 2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010 |
| Publisher | IEEE |
| Pages | 775-779 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781861353696 |
| ISBN (Print) | 9781424488582 |
| Publication status | Published - 20 Sept 2010 |
| Event | 2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010 - Newcastle upon Tyne, United Kingdom Duration: 21 Jul 2010 → 23 Jul 2010 |
Conference
| Conference | 2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010 |
|---|---|
| Country/Territory | United Kingdom |
| City | Newcastle upon Tyne |
| Period | 21/07/10 → 23/07/10 |
Keywords
- Content-based image retrieval (CBIR)
- Effective mapping
- Patch characterizing
- Patch recognizing
- Patch sampling
- Review
- Semantic concept