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harmonic transforms (PHTs) are a set of 2D transforms, which are based on a set of orthogonal projection bases, to generate a set of features which are invariant to rotation. PHTs represent a set of transforms whose kernels are basic waves and harmonic in nature. In this paper, Polar harmonic transforms (PHTs) are analyzed for rotation invariance and two equations are compared, namely, Polar Complex Exponential Transform (PCET) and Polar Cosine Transform (PCT), based on different parameters like Euclidean distance, False Rejection Rate (FRR) and False Acceptance Rate (FAR). Out of these two equations, Polar Cosine Transform (PCT) shows better results. The polar harmonic equations perform well in presence of rotation. Orthogonal kernels of PHTs are more effective in terms of information compactness and minimal information redundancy. Keywordsharmonic transforms, Polar complex exponential transform, Polar cosine transform, Fingerprint recognition and matching, Poroscopy, marker controlled watershed Segmentation, False acceptance rate, False rejection rate, Euclidean distance.

Implementation and Analysis of Multiple Polar Harmonic Equations in a Rotatory Two Dimensional Graphical Plane for Thumb Pore Identification