Search results for "Image Segmentation"
showing 10 items of 234 documents
MRF Model-Based Approach for Image Segmentation Using a Chaotic MultiAgent System
2006
In this paper, we propose a new Chaotic MultiAgent System (CMAS) for image segmentation. This CMAS is a distributed system composed of a set of segmentation agents connected to a coordinator agent. Each segmentation agent performs Iterated Conditional Modes (ICM) starting from its own initial image created initially from the observed one by using a chaotic mapping. However, the coordinator agent receives and diversifies these images using a crossover and a chaotic mutation. A chaotic system is successfully used in order to benefit from the special chaotic characteristic features such as ergodic property, stochastic aspect and dependence on initialization. The efficiency of our approach is s…
Routing Design in Wireless Sensor Networks and a Solution for Healthcare Environments
2011
This work presents the software implementation of a tissue engineering image analysis tool through the study of several biomaterials by means of different microscopy techniques (optical, scanning electron, and atomic force microscopy). With this tool, different quantitative information has been extracted from the microscopy image analysis of these biomaterials, as the number of objects, their mean size and the area they cover. Morphological characteristics, as the roundness or the porosity have been also obtained. All these quantitative information has permitted an statistical analysis over the obtained results.
Snapshot RGB mapping of skin melanin and hemoglobin.
2015
The concept of snapshot red-green-blue (RGB) multispectral imaging was applied for skin chromophore mapping. Three monochromatic spectral images have been extracted from a single RGB image dataset at simultaneous illumination of skin by 473-, 532-, and 659-nm laser lines. The spectral images were further transformed into distribution maps of skin melanin, oxyhemoglobin, and deoxyhemoglobin, related to pigmented and vascular skin malformations. The performance and clinical potential of the proposed technique are discussed
An application of neural networks to natural scene segmentation
2006
This paper introduces a method for low level image segmentation. Pixels of the image are classified corresponding to their chromatic features.
A Survey on Microaneurysms Detection in Color Fundus Images
2020
Early Detection of Microaneurysms (MA) plays a vital role in preventing the blindness caused by diabetic retinopathy (DR). DR is preventable yet a serious diabetic problem. Treatment at an earlier stage reduces the risk of blindness. Microaneurysm is the first sign of DR found in fundus images while doing screening. Detection of MA is a challenging task mainly because of its size. MA appears as a tiny red spot ranging from 15µm to 60µm size. The most common way to detect the MA from a colour fundus image is by classification/segmentation through machine learning and deep learning approaches. The FROC-based performance evaluation shows that the existing methods can reach only up to 80% of se…
Performance evaluation of simple fingerprint minutiae extraction algorithm using crossing number on valley structure
2008
In fingerprint recognition system, performance of fingerprint feature extraction algorithm is important. We use visual analysis to evaluate this performance. 100 respondents fill a questionnaire consisting of 30 images from fingerprint feature extraction process. We get 12,3 % minutiae points missed by this algorithm. With BOZORTH3 minutiae matching algorithm, the distribution of matching score of 80-fingerprint images are presented and we obtain EER 5.89 % at threshold value 180.
Fingerprint image enhancement using directional morphological filter
2005
Fingerprint images quality enhancement is a topic phase to ensure good performance in an automatic fingerprint identification system (AFIS) based on minutiae matching. In this paper a new fingerprint enhancement algorithm based on morphological filter is introduced. The algorithm is based on three steps: directional decomposition, morphological filter and composition. The performance of the proposed approach has been evaluated on two sets of images: the first one is DB3 database from Fingerprint Verification Competition (FVC) and the second one is self collected using an optical scanner
Real-Time Monocular Pose Estimation of 3D Objects Using Temporally Consistent Local Color Histograms
2017
We present a novel approach to 6DOF pose estimation and segmentation of rigid 3D objects using a single monocular RGB camera based on temporally consistent, local color histograms. We show that this approach outperforms previous methods in cases of cluttered backgrounds, heterogenous objects, and occlusions. The proposed histograms can be used as statistical object descriptors within a template matching strategy for pose recovery after temporary tracking loss e.g. caused by massive occlusion or if the object leaves the camera’s field of view. The descriptors can be trained online within a couple of seconds moving a handheld object in front of a camera. During the training stage, our approac…
Isolation of the left atrial surface from cardiac multi-detector CT images based on marker controlled watershed segmentation
2006
The delineation of left atrium (LA) and pulmonary veins (PVs) anatomy from high resolution images holds importance for atrial fibrillation (AF) investigation and treatment. In this study, a semiautomatic segmentation procedure for LA and PVs inner surface from contrast enhanced CT data was developed. The procedure consists of a three dimensional marker controlled watershed segmentation applied to the external morphological gradient, followed by variable threshold surface extraction from the original intensity image. A preliminary anisotropic non-linear filtering was implemented to improve the S/N ratio of CT images. The performance of segmentation was evaluated on cardiac CT scans of 12 AF …
Contribution to a marker-free system for human motion analysis
2002
This paper presents a novel approach to human gait analysis using a marker-free system. The devised acquisition system is composed of three synchronized and calibrated charge coupled device cameras. The aim of this work is to recognize in gray level image sequences the leg of a walking human and to reconstruct it in the three-dimensional space. An articulated threedimensional (3D) model of the human body, based on the use of tapered superquadric curves, is first introduced. A motion-based segmentation, using morphological operators, is then applied to the image sequences in order to extract the boundaries of the leg in motion. A reconstruction process, based on the use of a least median of …