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.
| Original language | English (US) |
|---|---|
| Pages | [d]754-757 |
| State | Published - 2000 |
| Event | International Conference on Image Processing (ICIP 2000) - Vancouver, BC, Canada Duration: Sep 10 2000 → Sep 13 2000 |
Other
| Other | International Conference on Image Processing (ICIP 2000) |
|---|---|
| Country/Territory | Canada |
| City | Vancouver, BC |
| Period | 9/10/00 → 9/13/00 |
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering