Content-Based Image Retrieval Based on Rectangular Segmentation

In this paper, we present a new framework for effective content-based image retrieval (CBIR) based on rectangular segmentation. In image segmentation, speed is more important than accuracy in CBIR. We propose a new rectangular approximate image segmentation to solve the problem. We also develop a significance function to reflect the importance of different position in image, and improve the segmentation and retrieval performance. Finally, we present a similarity measure between images with multi-objects. Experimental results show that the proposed method is more efficient and achieves higher precision on image retrieval of a large dataset. Key-Words: Color quantization, color similarity, image retrieval, image segmentation, rectangular segmentation.