The aim of the paper is to remove the noise in the images and at the same time to preserve the edges, fine details and texture in the image. This paper proposes a novel Adaptive Neuro Fuzzy Inference System (ANFIS) filter to remove impulse, Gaussian and mixed noise without affecting edges and texture of an image. It is a hybrid filter constructed by combining an appropriate noise filter, an edg...

We propose a computational step, called surround suppression, to improve detection of object contours and region boundaries in natural scenes. This step is inspired by the mechanism of non-classical receptive field inhibition that is exhibited by most orientation selective neurons in the primary visual cortex and that influences the perception of groups of edges or lines. We illustrate the prin...

Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. To extract important information from an MRI medical images, an efficient image segmentation or edge detection is required. Edges are represented as important contour features in the medical image since they are the boundaries where...

Retinal layer thickness measurement offers important information for reliable diagnosis of retinal diseases and for the evaluation of disease development and medical treatment responses. This task critically depends on the accurate edge detection of the retinal layers in OCT images. Here, we intended to search for the most suitable edge detectors for the retinal OCT image segmentation task. The...

This paper presents a hybrid approach to face detection and feature extraction. The remarkable advancement in technology has enhanced the use of more accurate and precise methods to detect faces. This paper presents a combination of three well known algorithms ViolaJones face detection framework, Neural Networks and Canny edge detection method to detect face in static images. The proposed work ...

Edges are often considered as primary image artifacts for extraction by low-level processing techniques, and the starting point for many computer vision techniques. As a result, reliable edge detection has long been a research goal. This paper describes initial investigations into recovering reliable edges using curvature models. Essentially, we modify Canny’s edge detector, using a curvature c...

Edge detection is one of the most commonly used and one of the most important operations in image processing which reduces the useless information while retaining the important structural properties of an image. Here a comparative study of Sobel, Roberts, Prewitt, LoG, Canny, Zerocross algorithms are conducted and corner points using Harris Corner detection algorithm on the image are obtained a...

In this paper the important problem is to understand the fundamental concepts of various filters and apply these filters in identifying a shark fish type which is taken as a case study. In this paper the edge detection techniques are taken for consideration. The software is implemented using MATLAB. The main two operators in image processing are Gradient and Laplacian operators. The case study ...

In this paper a novel algorithm which is based on hamming code and 2 k correction is proposed. The new method also utilizes canny edge detection and coherent bit length. Firstly, canny edge detector is applied to detect the edge of cover image and only edge pixels are selected for embedding payload. In order to enhance security, the edge pixels are scrambled. Then hamming encoding is practiced ...