Thresholding based iterative algorithms have the trade-off between effectiveness and optimality. Some are effective but involving sub-matrix inversions in every step of iterations. For systems of large sizes, such algorithms can be computationally expensive and/or prohibitive. The null space tuning algorithm with hard thresholding and feedbacks (NST+HT+FB) has a mean to expedite its procedure b...

A single thresholding technique may not provide the best binarization for all images of datasets such as protein crystallization images. To overcome this limitation, multiple thresholding methods are used to binarize images. Whenever multiple thresholding techniques are used, it is important to know which one provides the best result automatically. To solve this problem, in this study, we propo...

skin cancer has been the most usual and illustrates 50% of all new cancers detected each year. if they detected at an early stage, treatment can become simple and economically. accurate skin lesion segmentation is important in automated early skin cancer detection and diagnosis systems. the aim of this study is to provide an effective approach to detect the skin lesion border on a purposed imag...

Image thresholding is a challenging task in image processing field. Many efforts have already been made to propose universal, robust methods to handle a wide range of images. This paper introduces a new optimization-based thresholding approach. The optimizer, Differential Evolution (DE) algorithm, minimizes dissimilarity between the input grey-level image and the bi-level (thresholded) image. T...

After highlighting vessel like structure by an appropriate filter in Matched Filter (MF) technique, thresholding strategy is needed for the automated detection of blood vessels in retinal images. For the purpose, we propose to use a new technique of entropic thresholding based on Gray Level Spatial Correlation (GLSC) histogram which takes into account the image local property. Results obtained ...

Thresholding process is a fundamental image processing method. Typical thresholding methods are based on partitioning pixels in an image into two clusters. A new thresholding method is presented, in this paper. The main contribution of the proposed approach is the detection of an optimal image threshold exploiting the empirical mode decomposition (EMD) algorithm. The EMD algorithm can decompose...