Abstract
In this paper, we propose a new image annotation method by combining content-based image annotation and tag-based image annotation techniques. Content-based image annotation technique is adopted to extract 'loosely defined concepts' by analyzing pre-given images' features such as color moment (CM), edge orientation histogram (EOH), and local binary pattern (LBP), followed by constructing a set of SVMs for 100 loosely defined concepts. A base-vector for each concept, similar to tag-based image annotation technique, is then constructed by using SVMs' predicted probabilistic results for sample-images whose main concepts are known. Finally cosine similarity between a query-image vector and the base vector is calculated for each concept. Experimental results show that our proposed method outperforms content-based image annotation technique by about 23% in accuracy.
Original language | English |
---|---|
Title of host publication | Proceedings - 10th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 272-276 |
Number of pages | 5 |
ISBN (Electronic) | 9781479979783 |
DOIs | |
Publication status | Published - 2014 |
Event | 10th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2014 - Marrakech, Morocco Duration: 2014 Nov 23 → 2014 Nov 27 |
Other
Other | 10th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2014 |
---|---|
Country | Morocco |
City | Marrakech |
Period | 14/11/23 → 14/11/27 |
Keywords
- image annotation
- support vector machine
- vector space model
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Signal Processing
- Computer Networks and Communications