- Title
- Human perception based image retrieval using emergence index and fuzzy similarity measure
- Creator
- Deb, Sagarmay; Kulkarni, Siddhivinayak
- Date
- 2007
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/54597
- Identifier
- vital:3590
- Identifier
-
https://doi.org/10.1109/ISSNIP.2007.4496870
- Identifier
- ISBN:9781424415014
- Abstract
- The main concern dealing with content-based image retrieval (CBIR) is to bridge the semantic gap. The high level query posed by the user and low level features extracted by the machine illustrates the problem of semantic gap. To solve the problem of semantic gap, this paper presents a hybrid technique using an emergence index and fuzzy logic for efficient retrieval of images based on the colour feature. Emergence index (EI) is proposed to understand the hidden meaning of the image. Fuzzy similarity measure is developed to calculate the similarity between the target image and the images in the database. The images were ranked based on their similarity along with the fuzzy similarity distance measure. The preliminary experiments conducted on small set of images and promising results were obtained.
- Publisher
- Melbourne, Victoria : IEEE
- Relation
- Paper presented at 3rd International Conference on Intelligent Sensors, Sensor Networks and Information, ISSNIP 2007, Melbourne, Victoria : 3rd-6th December 2007 p. 359-363
- Rights
- Copyright IEEE
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0902 Automotive Engineering; Content-based retrieval; Feature extraction; Fuzzy set theory; Image retrieval; Visual databases
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