Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
The curvelet transform for image denoising
IEEE Transactions on Image Processing
A review on automatic image annotation techniques
Pattern Recognition
Rotation Invariant Curvelet Features for Region Based Image Retrieval
International Journal of Computer Vision
Structural image retrieval using automatic image annotation and region based inverted file
Journal of Visual Communication and Image Representation
Hi-index | 0.00 |
Region based image retrieval has received significant attention from recent researches because it can provide local description of images, object based query, and semantic learning. In this paper, we apply curvelet transform to region based retrieval of color images. The curvelet transform has shown promising result in image de-noising, character recognition, and texture image retrieval. However, curvelet feature extraction for segmented regions is challenging because it requires regular (e.g., rectangular) shape images or regions, while segmented regions are usually irregular. An efficient method is proposed to convert irregular regions to regular regions. Discrete curvelet transform can then be applied on these regular shape regions. Experimental results and analyses show the effectiveness of the proposed shape transform method. We also show the curvelet feature extracted from the transformed regions outperforms the widely used Gabor features in retrieving natural color images.