Image thresholding is used to segment an image into background and foreground using a given threshold. The threshold can be generated specific algorithm instead of pre-defined value obtained from observation or experiment. However, the involves per pixel operation, histogram calculation, iterative procedure search optimum that costly for high-resolution images. In this research, parallel implem...

Multilevel thresholding is an important technique for image processing and pattern recognition. The maximum entropy thresholding (MET) has been widely applied in the literature. In this paper, a new multilevel MET algorithm based on the technology of the shuffled frog-leaping (SFLO) algorithm is proposed: called the maximum entropy based shuffled frog-leaping algorithm thresholding (MESFLOT) me...

The proposed binarization is a scheme of parting a image pixel values into two classes black as foreground and white pixels as background then the thresholding is found for well known scheme for document image binarization. In this proposed work for the decomposition of both global and local thresholding this basic thresholding value we can use further. Here the global thresholding scheme is ef...

In this paper, a new algorithm for edge detection based on fuzzyconcept is suggested. The proposed approach defines dynamic membershipfunctions for different groups of pixels in a 3 by 3 neighborhood of the centralpixel. Then, fuzzy distance and -cut theory are applied to detect the edgemap by following a simple heuristic thresholding rule to produce a thin edgeimage. A large number of experime...

An improved pixon-based method is proposed in this paper for image segmentation. In thisapproach, a wavelet thresholding technique is initially applied on the image to reduce noise and toslightly smooth the image. This technique causes an image not to be oversegmented when the pixonbasedmethod is used. Indeed, the wavelet thresholding, as a pre-processing step, eliminates theunnecessary details...

We introduce a new iterative algorithm to find sparse solutions of underdetermined linear systems. The algorithm, a simple combination of the Iterative Hard Thresholding algorithm and of the Compressive Sampling Matching Pursuit or Subspace Pursuit algorithms, is called Hard Thresholding Pursuit. We study its general convergence, and notice in particular that only a finite number of iterations ...

the aim of this paper is to improve the performance of the conventional goertzel algorithm in determining the protein codingregions in deoxyribonucleic acid (dna) sequences. first, the symbolic dna sequences are converted into numerical signals usingelectron ion interaction potential method. then by combining the modified anti-notch filter and linear predictive coding model,we proposed an effic...

This paper presents a new image denoising algorithm based on local variance estimation. In the process of denoising, the Wiener filter is used to remove the noise component of the dual-tree complex wavelet transform (DT-CWT) coefficients. The variances of noise-free coefficients are estimated by the DT-CWT coefficients transformed by modified thresholding. The tests show that the proposed metho...