The objective of this paper is to propose an adaptive-evolutionary method for thresholding which is used as an artificial intelligent algorithm for image segmentation especially for object segmentation. This method employs resistant versus mixed histograms because of its suitable fitness function selection that consists of the histogram details. As things develop in the paper, three evolutionar...

We propose a comprehensive method for segmenting the retinal vasculature in fundus camera images. Our method does not require preprocessing and training and can therefore be used directly on different images sets. We enhance the vessels using matched filtering with multiwavelet kernels (MFMK), separating vessels from clutter and bright, localized features. Noise removal and vessel localization ...

This study compares the effectiveness of various image enhancement filters for improving the perceived visibility of coloured digital natural images for people with visual impairment. Generic filters were compared with Peli's adaptive enhancement and adaptive thresholding and custom-devised filters based on each subject's contrast sensitivity loss. Subjects with low vision made within filter ra...

This paper describes a novel global-to-local method for the adaptive enhancement and unsupervised segmentation of brain tissues in MRI (Magnetic Resonance Imaging) images. Three brain tissues are of interest: CSF (CerebroSpinal Fluid), GM (Gray Matter), WM (White Matter). Firstly, we de-noise the image using wavelet thresholding, and segment the image with minimum error thresholding. Both the t...

Estimation of large covariance matrices has drawn considerable recent attention, and the theoretical focus so far has mainly been on developing a minimax theory over a fixed parameter space. In this paper, we consider adaptive covariance matrix estimation where the goal is to construct a single procedure which is minimax rate optimal simultaneously over each parameter space in a large collectio...

The SAR and SAS images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. If the background of an image is uneven, the fixed thresholding technique is not suitable to segment an image using adaptive thresholding method. In this paper a new Adaptive thresholding method is proposed to reduce the speckle noise, preserving the structural...

In this paper, we present a novel semi-supervised smooth harmonic transductive learning algorithm that can get closed-form solution. Our method introduces the unlabeled class information to the learning process and tries to exploit the similar configurations shared by the label distribution of data. After discovering the property of smooth harmonic function based on spectral clustering in class...

We develop three novel wavelet domain denoising methods for subband-adaptive, spatiallyadaptive and multivalued image denoising. The core of our approach is estimation of the probability that a given coefficient contains a significant noise-free component, which we call “signal of interest”. In this respect we analyze cases where the probability of signal presence is (i) fixed per subband, (ii)...

Transmission Control Protocol Synchronized (SYN) flooding contributes to a major part of the Denial service attacks (Dos) because easy exploit nature TCP three way handshake mechanism. Attackers use this weakness overflow queue server and make its re-sources consumed resulting it be unavailable for requests legitimate users. So we are in need quick precise defence mechanism detect TCP-SYN Flood...