Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8544
Title: Water reflection recognition based on motion blur invariant moments in curvelet space
Authors: Zhong, SH
Liu, Y 
Liu, Y
Li, CS
Keywords: Imperfect symmetry
Invariant moments
Motion blur
Reflection axis detection
Water reflection
Issue Date: 2013
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on image processing, 2013, v. 22, no. 11, 6553236, p. 4301-4313 How to cite?
Journal: IEEE transactions on image processing 
Abstract: Water reflection, a typical imperfect reflection symmetry problem, plays an important role in image content analysis. Existing techniques of symmetry recognition, however, cannot recognize water reflection images correctly because of the complex and various distortions caused by the water wave. Hence, we propose a novel water reflection recognition technique to solve the problem. First, we construct a novel feature space composed of motion blur invariant moments in low-frequency curvelet space and of curvelet coefficients in high-frequency curvelet space. Second, we propose an efficient algorithm including two sub-algorithms: low-frequency reflection cost minimization and high-frequency curvelet coefficients discrimination to classify water reflection images and to determine the reflection axis. Through experimenting on authentic images in a series of tasks, the proposed techniques prove effective and reliable in classifying water reflection images and detecting the reflection axis, as well as in retrieving images with water reflection.
URI: http://hdl.handle.net/10397/8544
ISSN: 1057-7149
EISSN: 1941-0042
DOI: 10.1109/TIP.2013.2271851
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