A novel perceptual dissimilarity measure for image retrieval
conference contribution
posted on 2018-01-01, 00:00authored byH Shojanazeri, D Zhang, S Wei Teng, Sunil AryalSunil Aryal, G Lu
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.
History
Pagination
1-6
Location
Auckland, New Zealand
Start date
2018-11-19
End date
2018-11-21
ISSN
2151-2205
Language
eng
Publication classification
E1.1 Full written paper - refereed
Copyright notice
2018, IEEE
Title of proceedings
IVCNZ 2018 : International Conference on Image and Vision Computing New Zealand
Event
Image and Vision Computing New Zealand. International Conference (2018 : Auckland, New Zealand)