PERFORMANCE ANALYSIS OF WAVELET & BLUR INVARIANTS FOR CLASSIFICATION OF AFFINE AND BLURRY IMAGES

Image degradation occurs while acquisition because of so many reasons for example low illumination, noise, occlusion etc. Geometric distortion and rad iometric degradations are also one of the widesprea d difficulties in computer vision. This paper present s a system to classify multi class images deformed due to geometrical transform, blur contamination or the co mbination of both. Different blur and affined invar iant moment descriptors in spatial domain are used to ta ckle this problem, which are invariant to centrally symmetric blurs. In this paper, performance of the proposed system is analyzed in contrast to wavelet feature based system. The performance of the system is demonstrated through various experiments. Experimental results exhibits that method is effect ive and computationally inexpensive and can be appl ied to images having several geometrical and blur degra dation in the same image.

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