Low-dimensional shape index using color feature for Content-based image retrieval
Main Article Content
Abstract
A low-dimensional shape based indexing technique is used for achieving efficient and effective retrieval performance. This paper present a simple index based on shape features of regions that are segmented out of images based on color. A new shape similarity measure conforming to human perception is applied and shown to be effective. Low-level visual features like color, shape, texture, etc are being used for representing and retrieving images in many Content-Based Image Retrieval systems. Generally such methods suffer from the problems of high dimensionality leading to more computational time and inefficient indexing and retrieval performance. Images are segmented to obtain homogeneous color regions that are dominant and similar images form an image cluster stored in a hash structure. Each region within an image is then indexed by a region-based shape index. The shape index is invariant to translation, rotation and scaling. The retrieval performance is studied and compared with that of a region-based shape-indexing scheme.
Keywords: Content-Based Image Retrieval, low-dimensional, Color based image.
Downloads
Article Details
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.