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Two novel threshold techniques are proposed for image segmentation which is a very critical task in any image processing. The two methods are based in scanning each image row by row and to find the proper threshold value. A modification of this method is developed to find the threshold value by average. The two methods are implemented on a mammogram and accordingly, a comparison between the two methods is carried out.

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International audienceIn this letter, an efficient stepsize selection strategy for Givens parametrization-based independent component analysis (ICA) approaches is presented. The method is an extension of the pioneering deflationary ICA algorithm introduced by Delfosse and Loubaton (DelL(R)). The methodology underlying the computation of such a stepsize is based on sampling the contrast function using the information carried by its frequency components. Epileptic ElectroEncephaloGraphy (EEG)-based simulations show that the proposed approach stands for the best extraction accuracy/numerical complexity tradeoff with 15 times faster execution time. This is compared to a deterministic implementation of the DelLR technique and its recently proposed Jacobi-based variant, namely the JDICA method

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