Abstract
In this paper, we propose an extension to the local binary patterns for image retrieval. We focus on the spatial distribution information in images, and present a spatial-distribution-information-enhanced local pattern for content-based image retrieval. Differing from traditional local patterns, we group those gray-level varying values according to three directions, and each group is then merged into a local spatial distribution pattern to represent the spatial distribution property of the image. Our preliminary experimental results on a real dataset demonstrate the effectiveness of our algorithm.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
