Abstract. This paper addresses the representation of binary images using mathematical morphology, a nonlinear theory for image processing, based on set theory. The new image representation, called "five-step" skeleton representation, is an extension of the morphological binary skeleton. It consists of calculating the morphological digital binary skeleton using squares or crosses and then reiterating the above procedure for skeleton subsets using lines (horizontal, vertical, 45°and 135°
A precise and efficient quantized multiple sinusoids signal estimation algorithm is presented. For different initial conditions obtained using classical spectral estimation algorithms the final solution of our algorithm is not unique. We start to minimize a nonlinear cost function. The accuracy of the initial values of iterations has a large influence on the speed of convergence. An iterative process is performed to reduce the cost function. Algorithm stops when quantization conditions are satisfied. Our algorithm is computationally efficient.
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