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 radiometric degradations are also one of the widespread difficulties in computer vision. This paper presents a system to classify multi class images deformed due to geometrical transform, blur contamination or the combination of both. Different blur and affined invariant moment descriptors in spatial domain are used to tackle 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 effective and computationally inexpensive and can be applied to images having several geometrical and blur degradation in the same image.