# Texture image retrieval using a classification and contourlet-based features

arXiv: https://arxiv.org/abs/2403.06048 · HTML: https://mlsanity.com/paper/2403.06048/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 16 references that are in the map.
- First posted on arXiv 10 Mar 2024.

## Abstract (arXiv)

In this paper, we propose a new framework for improving Content Based Image Retrieval (CBIR) for texture images. This is achieved by using a new image representation based on the RCT-Plus transform which is a novel variant of the Redundant Contourlet transform that extracts a richer directional information in the image. Moreover, the process of image search is improved through a learning-based approach where the images of the database are classified using an adapted similarity metric to the statistical modeling of the RCT-Plus transform. A query is then first classified to select the best texture class after which the retained class images are ranked to select top ones. By this, we have achieved significant improvements in the retrieval rates compared to previous CBIR schemes.