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Blurred Image Recognition by Legendre Moment Invariants

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6 Author(s)
Hui Zhang ; Laboratory of Image Science and Technology, Department of Computer Science and Engineering, Southeast University, Centre de Recherche en Information Biomédicale Sino-Français (CRIBs), China ; Huazhong Shu ; Guoniu N. Han ; Gouenou Coatrieux
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Processing blurred images is a key problem in many image applications. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments. In this paper, we propose a new method to construct a set of blur invariants using the orthogonal Legendre moments. Some important properties of Legendre moments for the blurred image are presented and proved. The performance of the proposed descriptors is evaluated with various point-spread functions and different image noises. The comparison of the present approach with previous methods in terms of pattern recognition accuracy is also provided. The experimental results show that the proposed descriptors are more robust to noise and have better discriminative power than the methods based on geometric or complex moments.

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IEEE Transactions on Image Processing  (Volume:19 ,  Issue: 3 )