The content-based image retrieval (CBIR) is the most acceptable method often used in an image retrieval system because it can manage image database efficiently and effectively. The CBIR methods usually retrieve the images by image features. In this paper, we exploit a region called affine invariant region (AIR) as an image feature to help effectively retrieve the images even when the images have been attacked or processed. Moreover, we use vector quantization (VQ) to reduce the comparison of image features for improving the retrieval efficiency. The experimental results show that the method has a higher recall rate, lower retrieval time, and promising accuracy.
|Number of pages||21|
|Journal||Journal of Network Intelligence|
|Publication status||Published - Aug 2018|
- content-based image retrieval (CBIR)
- affine invariant region (AIR)
- vector quantization (VQ)
Lee, C-F., Wang, Y-J., Chu, S-C., & Roddick, J. (2018). An adaptive content-based image retrieval method exploiting an affine invariant region based on a VQ-applied quadtree robust to geometric distortions. Journal of Network Intelligence, 3(3), 214-234. https://www.semanticscholar.org/paper/An-Adaptive-Content-Based-Image-Retrieval-Method-an-Lee-Wang/6b19b70bda1ac870c49649fadc1a27a71fadadb0