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A Co-processor for Computing the Euler Number of a Binary Image using Divide-and-Conquer Strategy

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Dey S. , Bhattacharya B. B. , Kundu M. K. , Bishnu A. , Acharya T.

tom Vol. 76, nr 1-2

75-89

Euler number is a fundamental topological feature of an image. The efficiency of computation of topological features of an image is critical for many digital imaging applications such as image matching, database retrieval, and computer vision that require real time response. In this paper, a novel algorithm for computing the Euler number of a binary image based on divide-and-conquer paradigm, is proposed, which outperforms significantly the conventional techniques used in image processing tools. The algorithm can be easily parallelized for computing the Euler number of an N ×N image in O(N) time, with O(N) processors. Using a simple architecture, the proposed method can be implemented as a special purpose VLSI chip to be used as a co-processor.

A New Probabilistic Approach for Fractal Based Image Compression

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Mitra S. K. , Kundu M. K. , Murthy C. A. , Bhattacharya B. B. , Acharya T.

2008

tom Vol. 87, nr 3-4

417-433

Approximation of an image by the attractor evolved through iterations of a set of contractive maps is usually known as fractal image compression. The set of maps is called iterated function system (IFS). Several algorithms, with different motivations, have been suggested towards the solution of this problem. But, so far, the theory of IFS with probabilities, in the context of image compression, has not been explored much. In the present article we have proposed a new technique of fractal image compression using the theory of IFS and probabilities. In our proposed algorithm, we have used a multiscaling division of the given image up to a predetermined level or up to that level at which no further division is required. At each level, the maps and the corresponding probabilities are computed using the gray value information contained in that image level and in the image level higher to that level. A fine tuning of the algorithm is still to be done. But, the most interesting part of the proposed technique is its extreme fastness in image encoding. It can be looked upon as one of the solutions to the problem of huge computational cost for obtaining fractal code of images.