- Title
- A novel perceptual dissimilarity measure for image retrieval
- Creator
- Shojanazeri, Hamid; Zhang, Dengsheng; Teng, Shyh; Aryal, Sunil; Lu, Guojun
- Date
- 2018
- Type
- Text; Conference proceedings; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/168584
- Identifier
- vital:13872
- Identifier
-
https://doi.org/10.1109/IVCNZ.2018.8634763
- Identifier
- ISBN:21512191 (ISSN); 9781728101255 (ISBN)
- Abstract
- Similarity measure is an important research topic in image classification and retrieval. Given a type of image features, a good similarity measure should be able to retrieve similar images from the database while discard irrelevant images from the retrieval. Similarity measures in literature are typically distance based which measure the spatial distance between two feature vectors in high dimensional feature space. However, this type of similarity measures do not have any perceptual meaning and ignore the neighborhood influence in the similarity decision making process. In this paper, we propose a novel dissimilarity measure, which can measure both the distance and perceptual similarity of two image features in feature space. Results show the proposed similarity measure has a significant improvement over the traditional distance based similarity measure commonly used in literature.; International Conference Image and Vision Computing New Zealand
- Publisher
- IEEE Computer Society
- Relation
- 2018 International Conference on Image and Vision Computing New Zealand, IVCNZ 2018; Auckland, New Zealand; 19th-21st November 2018 Vol. 2018-November, p. 1-6
- Rights
- Copyright © 2018 IEEE.
- Rights
- This metadata is freely available under a CCO license
- Subject
- Dissimilarity measure; Image dissimilarity; Image retrieval; Perceptual dissimilarity
- Reviewed
- Hits: 3601
- Visitors: 3530
- Downloads: 1
| Thumbnail | File | Description | Size | Format |
|---|