Classification of Textured and Non-Textured Images Using Region Segmentation

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.

• Type: Conference
• Year: 2000
• Where: ICIP
• Authors: Jia Li, James Ze Wang, Gio Wiederhold
• Keywords: Content-based Image Retrieval, Corresponding Image Type, ICIP 2000, Image Processing, Textured Images