Water reflection recognition via minimizing reflection cost based on motion blur invariant moments

Authors:
Sheng-hua Zhong;Yan Liu;Ling Shao;Fu-lai Chung
Affiliations:
The Hong Kong Polytechnic University, Hong Kong, P. R. China;The Hong Kong Polytechnic University, Hong Kong, P. R. China;University of Sheffield, Sheffield, United Kingdom;The Hong Kong Polytechnic University, Hong Kong, P. R. China
Venue:
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Year:
2011

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Abstract

Water reflection, a kind of typical imperfect reflection symmetry problem, plays an important role in image content analysis. However, existing techniques of symmetry recognition cannot recognize water reflection images correctly because of the complex and various distortions caused by water wave. To address this difficulty, we construct a novel feature space which is composed of motion blur invariant moments. Moreover, we propose an efficient detection algorithm to determine the reflection axis in images with water reflection. By experimenting on real image dataset with different tasks, the proposed techniques demonstrate impressive results in the water reflection image classification, the reflection axis detection, and the retrieval of the images with water reflection.