An efficient indexing method for content-based image retrieval

Authors:
Deying Feng;Jie Yang;Congxin Liu
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China
Venue:
Neurocomputing
Year:
2013

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Abstract

In this paper, we propose an efficient indexing method for content-based image retrieval. The proposed method introduces the ordered quantization to increase the distinction among the quantized feature descriptors. Thus, the feature point correspondences can be determined by the quantized feature descriptors, and they are used to measure the similarity between query image and database image. To implement the above scheme efficiently, a multi-dimensional inverted index is proposed to compute the number of feature point correspondences, and then approximate RANSAC is investigated to estimate the spatial correspondences of feature points between query image and candidate images returned from the multi-dimensional inverted index. The experimental results demonstrate that our indexing method improves the retrieval efficiency while ensuring the retrieval accuracy in the content-based image retrieval.