A general paradigm for lifting binary morphological algorithms to fuzzy algorithms is employed to construct fuzzy versions of classical binary morphological operations. The lifting procedure is based upon an epistemological interpretation of both image and filter fuzzification. Algorithms are designed via the paradigm for various fuzzifications and their performances are analyzed to provide ins...

We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI) system. The NAVI has a single board processing system (SBPS), a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in und...

A new approach is proposed for the automatic detection of the near-end and far-end intima and adventitia inner boundaries in ultrasound images of the common carotid artery. This method uses the instantaneous coefficient of variation edge detector, fuzzy classification of edges, several discriminating features of the carotid wall boundaries and dynamic programming. The carotid wall boundaries ar...

In this article, a software for image indexing and retrieval is presented. The classification proposed here is based on the dominant color(s) of the images. The process consists in assigning a colorimetric profile to the image in HLS space (Hue, Lightness, Saturation). First, the definition of hue is done thanks to a fuzzy representation to take into account the non-uniformity of colors distrib...

This paper aims to develop a new methodology for monitoring forest disturbances and regrowth using ALOS PALSAR data in tropical regions. In the study, forest disturbances and regrowth were assessed between 2007 and 2010 in Vietnam, Cambodia and Lao People’s Democratic Republic. The deforestation rate in Vietnam has been among the highest in the tropics in the last few decades, and those in Camb...

In this paper we present a corner detection which makes use of eigenvalues of covariance matrices of different support regions over edge points. Edges are first extracted through the use of Canny edge detection, and then determine corners according to eigenvalues product of covariance matrices of the edge at various regions of support. Experimental results show that the proposed method has more...

Edge detection is a terminology in image processing and computer vision, particularly in the areas of feature detection and feature extraction, to refer to algorithms which aim at identifying points in a image. This paper highlights the ways to detect edges at five different levels which will help in pattern recognition and feature extraction with the use of fuzzy logic a method well known in A...

Edges detection in digital images is a problem that has been solved by means of the application of different techniques from digital signal processing, also the combination of some of these techniques with Fuzzy Inference System (FIS) has been experienced. In this work a new FIS Type-2 method is implemented for the detection of edges and the results of three different techniques for the same in...

The purpose of the paper is to compare the performance of various fuzzy edge detectors which have been optimized by Particle Swarm Optimization (PSO). Three different type edge detectors Classical fuzzy Heuristic (CFH), Gaussian rule based (GRBF) and Robust Fuzzy Complement (RFC) are used. These edge detectors are effective in detecting edges, however the edges are thick. This paper proposes th...

In this paper a comparative analysis of different techniques in order to transform a gray-scale edge image to a thin binary edge image is performed. Several thresholding methods and thinning methods are compared. The comparison is made according to some performance measures, such as Pratt’s figure of merit, Baddeley’s measure and the ρ-coefficient. This study is an essential intermediate step t...