Title
Sammatch: A Flexible And Efficient Sampling-Based Image Retrieval Technique For Large Image Databases
Abstract
The rapid growth of digital image data increases the need for efficient and effective image retrieval systems. Such systems should provide functionality that tailors to the user's need at the query time. In this paper, we propose a new image retrieval technique that allows users to control the relevantness of the results. For each image, the color contents of its regions are captured and used to compute similarity. Various factors, assigned automatically or by the user, allow high recall and precision to be obtained. We implemented the proposed technique for a large database of 16,000 images. Our experimental results show that this technique is not only space-time efficient but also more effective than recently proposed color histogram techniques.
Publication Date
12-1-1999
Publication Title
Proceedings of the ACM International Multimedia Conference & Exhibition
Number of Pages
225-234
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0033279535 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0033279535
STARS Citation
Hua, Kien A.; Vu, Khanh; and Oh, Jung Hwan, "Sammatch: A Flexible And Efficient Sampling-Based Image Retrieval Technique For Large Image Databases" (1999). Scopus Export 1990s. 4263.
https://stars.library.ucf.edu/scopus1990/4263