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Proceedings Paper

Perceptually based techniques for semantic image classification and retrieval
Author(s): Dejan Depalov; Thrasyvoulos Pappas; Dongge Li; Bhavan Gandhi
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Paper Abstract

The accumulation of large collections of digital images has created the need for efficient and intelligent schemes for content-based image retrieval. Our goal is to organize the contents semantically, according to meaningful categories. We present a new approach for semantic classification that utilizes a recently proposed color-texture segmentation algorithm (by Chen et al.), which combines knowledge of human perception and signal characteristics to segment natural scenes into perceptually uniform regions. The color and texture features of these regions are used as medium level descriptors, based on which we extract semantic labels, first at the segment and then at the scene level. The segment features consist of spatial texture orientation information and color composition in terms of a limited number of locally adapted dominant colors. The focus of this paper is on region classification. We use a hierarchical vocabulary of segment labels that is consistent with those used in the NIST TRECVID 2003 development set. We test the approach on a database of 9000 segments obtained from 2500 photographs of natural scenes. For training and classification we use the Linear Discriminant Analysis (LDA) technique. We examine the performance of the algorithm (precision and recall rates) when different sets of features (e.g., one or two most dominant colors versus four quantized dominant colors) are used. Our results indicate that the proposed approach offers significant performance improvements over existing approaches.

Paper Details

Date Published: 9 February 2006
PDF: 10 pages
Proc. SPIE 6057, Human Vision and Electronic Imaging XI, 60570Z (9 February 2006); doi: 10.1117/12.660612
Show Author Affiliations
Dejan Depalov, Northwestern Univ. (United States)
Thrasyvoulos Pappas, Northwestern Univ. (United States)
Dongge Li, Motorola Labs. (United States)
Bhavan Gandhi, Motorola Labs. (United States)

Published in SPIE Proceedings Vol. 6057:
Human Vision and Electronic Imaging XI
Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Scott J. Daly, Editor(s)

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