Abstract
Most of the content-based image retrieval systems focus on similarity-based retrieval of images by utilizing color, shape and texture features. For color-based image retrieval, the average color or color-histograms of images are widely used as feature vectors. In this paper, we propose a new searching scheme, called Fuzzy Membership Value-Indexing, to guarantee higher retrieval quality. This scheme allows us to retrieve images based on high-level emotional concepts, such as 'cool', 'soft', 'strong,' etc. Each image is automatically classified into predefined emotional categories, by analyzing its color values in HSI color space and assigning appropriate fuzzy membership values. Our experimental results show that the proposed technique can reflect user's searching intention more accurately.
Original language | English |
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Pages (from-to) | 361-365 |
Number of pages | 5 |
Journal | Lecture Notes in Computer Science |
Volume | 3597 |
DOIs | |
Publication status | Published - 2005 |
Event | 3rd International Conference on Human.Society@Internet - HSI 2005 - Tokyo, Japan Duration: 2005 Jul 27 → 2005 Jul 29 |
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science