Image retrieval based on fuzzy mapping of image database and fuzzy similarity distance
- Authors: Kulkarni, Siddhivinayak
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at 6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007, Melbourne, Victoria : 11th-13th July 2007 p. 812-817
- Full Text:
- Description: The on-line image retrieval process consists of a query example image, given by the user as an input, from which low-level image features are extracted. These image features are used to find images in the database which are most similar to the query image. A drawback, however, is that these low level image features are often too restricted to describe images on a conceptual or semantic level. The gap between the high level query from the user and low level features extracted by a computer is known as the semantic gap. Translating or converting the question posed by a human to the low level features seen by the computer illustrates the problem in bridging the semantic gap. This paper proposes a novel fuzzy approach for mapping the fuzzy database while extracting the colour features from image and assigning the weights to this fuzzy content when calculating the similarity between the query image and the images in database. Number of experiments was conducted on a small colour image database and promising results were obtained.
- Description: 2003005444
Image retrieval based on semantics of intra-region color properties
- Authors: Sajjanhar, Atul , Lu, Guojun , Zhang, Dengsheng , Zhou, Wanlei , Chen, Yi-Ping Phoebe
- Date: 2008
- Type: Text , Conference paper
- Relation: Proceedings of 2008 IEEE 8th International Conference on Computer and Information Technology p. 338-343
- Full Text: false
- Reviewed:
- Description: Traditional image retrieval systems are content based image retrieval systems which rely on low-level features for indexing and retrieval of images. CBIR systems fail to meet user expectations because of the gap between the low level features used by such systems and the high level perception of images by humans. Semantics based methods have been used to describe images according to their high level features. In this paper, we performed experiments to identify the failure of existing semantics-based methods to retrieve images in a particular semantic category. We have proposed a new semantic category to describe the intra-region color feature. The proposed semantic category complements the existing high level descriptions. Experimental results confirm the effectiveness of the proposed method