• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/

An Efficient Processing Technique for Similarity based Visual Queries


Jun Hwang, Journal of Internet Computing and Services, Vol. 1, No. 1, pp. 1-14, Nov. 2000
Full Text:

Abstract

Visual information retrieval and image databases are very important applications of spatial access methods. The quaries for these applications are visual and based not on exact match but on dubjective similarity. The individual aperations of spatial access methods are much more expensive than those of conventional one-dimensional access methods. Also, because the visual queries are much more complex than textual queries, an efficient processing technique for visual queries is one of the critical requirements in the development of large and scalable image databases. Therefore, efficient translation and execution for the complex visual queries are not less important than those of textual databases. In this paper, we introduce our cognitive and topological studies that are required to process subjective visual queries effectively. Then, we propose an efficient translation and execution techniques for similarity based visual queries by conducting these related studies.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from November 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[APA Style]
Hwang, J. (2000). An Efficient Processing Technique for Similarity based Visual Queries. Journal of Internet Computing and Services, 1(1), 1-14.

[IEEE Style]
J. Hwang, "An Efficient Processing Technique for Similarity based Visual Queries," Journal of Internet Computing and Services, vol. 1, no. 1, pp. 1-14, 2000.

[ACM Style]
Jun Hwang. 2000. An Efficient Processing Technique for Similarity based Visual Queries. Journal of Internet Computing and Services, 1, 1, (2000), 1-14.