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Presented in this paper is an evolutionary approach to the problem of CT image reconstruction: an evolutionary algorithm (EA) is used to reconstruct CT images from a limited number of projection data, where conventional methods (e.g. Algebraic Reconstruction Techniques ART) solution tends to be unsatisfactory. We use traditional as well as adapted genetic operators in our evolutionary approach to the CT image reconstruction problem. The evolutionary algorithm yielded good results that challenge the conventional ART.

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In the literature, several abscissae generation methods of chaff points in fingerprint fuzzy vault exist. In this paper, we make an experimental comparison between squares method and threshold methods. The experimental results show that the squares method is far better than methods based on threshold. But minutiae representation in squares method use 2D representation while threshold methods are represented by composite representation. We proposed to implements squares methods using composite representation and made same experiments which showed less gain of time.