Segmentation and histogram generation using the HSV color space for image retrieval
- 25 June 2003
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
We have analyzed the properties of the HSV (hue, saturation and value) color space with emphasis on the visual perception of the variation in hue, saturation and intensity values of an image pixel. We extract pixel features by either choosing the hue or the intensity as the dominant property based on the saturation value of a pixel. The feature extraction method has been applied for both image segmentation as well as histogram generation applications - two distinct approaches to content based image retrieval (CBIR). Segmentation using this method shows better identification of objects in an image. The histogram retains a uniform color transition that enables us to do a window-based smoothing during retrieval. The results have been compared with those generated using the RGB color space.Keywords
This publication has 8 references indexed in Scilit:
- NeTra: a toolbox for navigating large image databasesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- SIMPLIcity: semantics-sensitive integrated matching for picture librariesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2001
- Content-based image retrieval at the end of the early yearsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2000
- Blobworld: A System for Region-Based Image Indexing and RetrievalLecture Notes in Computer Science, 1999
- Supporting ranked Boolean similarity queries in MARSIEEE Transactions on Knowledge and Data Engineering, 1998
- QBIC project: querying images by content, using color, texture, and shapePublished by SPIE-Intl Soc Optical Eng ,1993
- Color indexingInternational Journal of Computer Vision, 1991
- Finding Groups in DataWiley Series in Probability and Statistics, 1990