Search results for "Computer vision"

Real-time people counting system using a single video camera

2008

This is the copy of journal's version originally published in Proc. SPIE 6811. Reprinted with permission of SPIE: http://spie.org/x10.xml?WT.svl=tn7 There is growing interest in video-based solutions for people monitoring and counting in business and security applications. Compared to classic sensor-based solutions the video-based ones allow for more versatile functionalities, improved performance with lower costs. In this paper, we propose a real-time system for people counting based on single low-end non-calibrated video camera. The two main challenges addressed in this paper are: robust estimation of the scene background and the number of real persons in merge-split scenarios. The latter…

Efficient Skin Detection under Severe Illumination Changes and Shadows

2011

International audience; This paper presents an efficient method for human skin color detection with a mobile platform. The proposed method is based on modeling the skin distribution in a log-chromaticity color space which shows good invariance properties to changing illumination. The method is easy to implement and can cope with the requirements of real-world tasks such as illumination variations, shadows and moving camera. Extensive experiments show the good performance of the proposed method and its robustness against abrupt changes of illumination and shadows.

Quantitative Geometric Three-Dimensional Reconstruction of Neuronal Architecture and Mapping of Labeled Proteins from Confocal Image Stacks

2014

Comparison of Statistical Methods for the Detection of Contrast Material in Echocardiographic Image Sequences

1987

Ultrasonic imaging of the heart is a diagnostic tool which is increasingly used in cardiology. In addition to the representation of important anatomical information two dimensional images provided by mechanical or electronically steered sector scanners can be used for the extraction of functional parameters of the heart (as e.g. enddiastolic volume or ejection fraction). A poor definition of the endocardial border especially resulting from the noisy appearance of the images and from qualitatively restricted echocardiograms leads to uncertainties in the quantitative analysis and therefore requires refined methods for the determination of functional parameters. Our investigations which are ba…

A Deep Learning Approach for Automated Fault Detection on Solar Modules Using Image Composites

2021

Aerial inspection of solar modules is becoming increasingly popular in automatizing operations and maintenance in large-scale photovoltaic power plants. Current practices are typically time-consuming as they make use of manual acquisitions and analysis of thousands of images to scan for faults and anomalies in the modules. In this paper, we explore and evaluate the use of computer vision and deep learning methods for automating the analysis of fault detection and classification in large scale photovoltaic module installations. We use convolutional neural networks to analyze thermal and visible color images acquired by cameras mounted on unmanned aerial vehicles. We generate composite images…

Hand Detection and Tracking Using the Skeleton of the Blob for Medical Rehabilitation Applications

2012

This article presents an image processing application for hand detection and tracking using the 4-connected skeleton of the segmentation mask. The system has been designed to be used with techniques of virtual reality to develop an interactive application for phantom limb pain reduction in therapeutic treatments. One of the major contributions is the design of a fast and accurate skeleton extractor, that has proven to be faster than those available in the literature. The skeleton allows the system to precisely detect the position of all the interest points of the hand (namely the fingers and the hand center). The system, composed of both the hand detector and tracker, and the virtual realit…

Ridge-line optimal detector

2000

Image processing techniques have seen many developments in recent years. Starting from the pioneering work of Canny, Deriche developed a second order recursive filter capable of detecting stepped contours. However, there are other contour shapes that those filters struggle to detect. We describe a new optimal filter sensu Canny for detecting ridge-line contours. This is a third order recursive and even filter. It is dependent on three parameters by which detection accuracy is adjusted. The results obtained by applying this filter to (possibly noise- affected) images are compared with those in the work by Ziou. © 2000 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(00)00706-6)

Feature selection using support vector machines and bootstrap methods for ventricular fibrillation detection

2012

Early detection of ventricular fibrillation (VF) is crucial for the success of the defibrillation therapy in automatic devices. A high number of detectors have been proposed based on temporal, spectral, and time-frequency parameters extracted from the surface electrocardiogram (ECG), showing always a limited performance. The combination ECG parameters on different domain (time, frequency, and time-frequency) using machine learning algorithms has been used to improve detection efficiency. However, the potential utilization of a wide number of parameters benefiting machine learning schemes has raised the need of efficient feature selection (FS) procedures. In this study, we propose a novel FS…

BioImageXD - Free Microscopy Image Processing Software

2008

Extended abstract of a paper presented at Microscopy and Microanalysis 2008 in Albuquerque, New Mexico, USA, August 3 – August 7, 2008

Reduction of the number of spectral bands in Landsat images: a comparison of linear and nonlinear methods

2006

We describe some applications of linear and nonlinear pro- jection methods in order to reduce the number of spectral bands in Land- sat multispectral images. The nonlinear method is curvilinear component analysis CCA, and we propose an adapted optimization of it for image processing, based on the use of principal-component analysis PCA, a linear method. The principle of CCA consists in reproducing the topol- ogy of the original space projection points in a reduced subspace, keep- ing the maximum of information. Our conclusions are: CCA is an im- provement for dimension reduction of multispectral images; CCA is really a nonlinear extension of PCA; CCA optimization through PCA called CCAinitP…