A NOVEL VISUAL CONTENT DESCRIPTOR USING COLOR AND SHAPE FEATURES

Le Hoang Thanh



DOI: 10.15625/vap.2016.0003

Abstract


Images contain information in a very dense and complex form, which a human eye, after years of training, can extract and understand. The main goal is to extract form an image a set of composing objects or real life attributes. This paper presents a novel framework for combining color and shape information, to achieve higher retrieval efficiency. The combination of the color and shape features provide a robust feature set for image retrieval. Two proposed methods – PGLAC (Pyramidal gradient local auto-correlations) and GCDD (Global color distribution descriptor) will be used as visual descriptors extracting spatial information of shape in the image. The experimental results demonstrate the efficacy of the proposed methods.

Keywords


Content-based image retrieval, visual descriptors, Gradient Local Auto-Correlations

Full Text:

PDF


Copyright (c) 2017 PROCEEDING of Publishing House for Science and Technology



PROCEEDING

PUBLISHING HOUSE FOR SCIENCE AND TECHNOLOGY

Website: http://vap.ac.vn

Contact: nxb@vap.ac.vn