Classification of textured and non-textured images using region segmentation

Author

Li, Jia ; Wang, James Ze ; Wiederhold, Gio

Author_Institution

Dept. of Comput. Sci., Stanford Univ., CA, USA

Volume

3

fYear

2000

fDate

2000

Firstpage

754

Abstract

The classification of general-purpose photographs into textured and non-textured images is critical for developing accurate content-based image retrieval systems for large-scale image databases. With the accurate detection of textured images, we may retrieve images based on features tailored for the corresponding image type. In this paper, we present an algorithm to classify a photographic image as textured or non-textured using region segmentation and statistical testing. The application of the system to a database of about 60,000 general-purpose images shows much improved accuracy in retrieval

Keywords

content-based retrieval; feature extraction; image classification; image retrieval; image segmentation; visual databases; classification; content-based image retrieval systems; features; general-purpose photographs; image type; large-scale image databases; nontextured images; photographic image; region segmentation; statistical testing; textured images; Biomedical informatics; Content based retrieval; Frequency; Image databases; Image retrieval; Image segmentation; Information retrieval; Large-scale systems; Partitioning algorithms; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2000. Proceedings. 2000 International Conference on

Conference_Location

Vancouver, BC

ISSN

1522-4880

Print_ISBN

0-7803-6297-7

Type

conf

DOI

10.1109/ICIP.2000.899564

Filename

899564