Title :
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
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;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.899564