SYMMETRY FEATURE IN CONTENT-BASED IMAGE RETRIEVAL (MA-P5)

Author(s) : Jingrui He (Tsinghua University, China) Mingjing Li (Microsoft Research Asia, China) Hongjiang Zhang (Microsoft Research Asia, China) Changshui Zhang (Tsinghua University, China)

Abstract : In this paper, we first apply the theory of wallpaper groups to natural images and extract a novel feature to depict the symmetry property of natural images. The original proposed algorithm takes autocorrelation and correlation as a preprocessing step, which is very time-consuming. Through further analysis, we develop a set of schemes to accelerate this algorithm. Experimental results demonstrate that in performing content-based image retrieval, the proposed symmetry feature outperforms wavelet feature, which is a widely accepted descriptor of texture, and water-filling feature. The accelerated version of the algorithm improves the processing speed by a large margin while it brings little degradation to retrieval performance.

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