Image Categorization Based on Computationally Economic LAB Colour Features

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 195)

Abstract

An easy to compute and small colour feature vector is introduced in this paper, as a tool to be used in the process of retrieval or classification of similarly coloured digital images from very large databases. A particular set of “ab” planes from the LAB colour system is used, along with a specific configuration of colour regions within them. The colour feature vector is low dimensional (only 96 components), computationally economic and performs very well on a carefully selected database of rose images, publicly available.

Keywords

image retrieval feature vector colour similarity colour classification agglomerative hierarchical algorithm 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institute of Computer ScienceThe Romanian AcademyIasiRomania

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