Search results for "Signal"
showing 10 items of 6924 documents
Use of H.264 real-time video encoding to reduce display wall system bandwidth consumption
2015
This paper compares the DXT and JPEG image compression techniques used in display wall solutions SAGE and DisplayCluster with hardware accelerated H.264 video encoding that is used in the display wall system developed by the authors of this paper. The obtained processing power usage and generated bandwidth measurements presented in this paper demonstrate that hardware accelerated H.264 encoding offers multiple benefits over software implemented H.264, DXT and JPEG.
Binarization of a super-resolving graytone pupil filter by digital halftoning
1995
— Six digital-halftoning procedures, including one algorithm proposed by us, are compared to determine which one is best suited to binarization of a parabolic super-resolving pupil filter. The procedures we deal with include iterative, error-diffusion, error-convergence, and 1-pixel algorithms. We carry out a numerically simulated experiment in which an object that consists of either one point source or two coherent point sources is imaged in a 4f imaging system with either a continuous super-resolving parabolic filter or one of its six different binary versions. The performance of binary filters is examined in terms of two parameters: the resemblance of their amplitude impulse response (AI…
Current characterisation for ultra low power wireless body area networks
2010
The emerging area of body area networks (BAN) imposes challenging requirements on hardware and software to achieve the desired lifetimes for certain devices such as long term medical implants. In this paper, we propose a novel approach to the measurement and characterisation of the energy consumption of BAN devices. The approach uses a low cost energy auditing circuit and addresses the problem of accurately measuring low-level current consumption. This new technique will allow precise and analytical measurements of systems and components in terms of energy. This will help circuit designers minimise power consumption in BAN devices. Software engineers might use this approach to validate and …
A microcomputer system for controlling classical conditioning experiments
1994
A microcomputer-based laboratory system for controlling stimulus presentations and data acquisition in classical conditioning experiments is described. The system comprises an Intel 386/486-based microcomputer and a commercially obtained low-cost counter/timer board with input/output lines for stimulus timing and external device control. A simple, yet versatile custom-designed structured programming language is provided for performing an unlimited number of stimulus configurations and their sequences. In electrophysiological studies, the system can be flexibly connected to computer-controlled signal conditioning systems for the amplification and filtering of multiunit and evoked field poten…
<title>Fast motion estimation based on spatio-temporal Gabor filters: parallel implementation on multi-DSP</title>
2000
The aim of our work is to implement a system of motion estimation in image sequences processing on DSP's: fast motion estimation based on Gabor spatio-temporal filters. Our approach consists to calculate optical flow using an energy-based method, named combined filtering which associates the energetic responses of Gabor spatio- temporal filters organized in triads. For this purpose, we applicate a technique developed by the Laboratory LIS in France, inspired from the architecture of Heeger. To reduce the computation time, we present also a parallel implementation of the algorithm on a multi-DSP architecture using SynDEx tool which is a programming environment to generate optimized distribut…
Directive local color transfer based on dynamic look-up table
2019
Abstract Color transfer in image processing usually suffers from misleading color mapping and loss of details. This paper presents a novel directive local color transfer method based on dynamic look-up table (D-DLT) to solve these problems in two steps. First, a directive mapping between the source and the reference image is established based on the salient detection and the color clusters to obtain directive color transfer intention. Then, dynamic look-up tables are created according to the color clusters to preserve the details, which can suppress pseudo contours and avoid detail loss. Subjective and objective assessments are presented to verify the feasibility and the availability of the…
Proposition of Convolutional Neural Network Based System for Skin Cancer Detection
2019
Skin cancer automated diagnosis tools play a vital role in timely screening, helping dermatologists focus on melanoma cases. Best arts on automated melanoma screening use deep learning-based approaches, especially deep convolutional neural networks (CNN) to improve performances. Because of the large number of parameters that could be involved during training in CNN many training samples are needed to avoid overfitting problem. Gabor filtering can efficiently extract spatial information including edges and textures, which may reduce the features extraction burden to CNN. In this paper, we proposed a Gabor Convolutional Network (GCN) model to improve the performance of automated diagnosis of …
No-reference mesh visual quality assessment via ensemble of convolutional neural networks and compact multi-linear pooling
2020
Abstract Blind or No reference quality evaluation is a challenging issue since it is done without access to the original content. In this work, we propose a method based on deep learning for the mesh visual quality assessment without reference. For a given 3D model, we first compute its mesh saliency. Then, we extract views from the 3D mesh and the corresponding mesh saliency. After that, the views are split into small patches that are filtered using a saliency threshold. Only the salient patches are selected and used as input data. After that, three pre-trained deep convolutional neural networks are employed for feature learning: VGG, AlexNet, and ResNet. Each network is fine-tuned and pro…
Towards General Purpose Object Detection: Deep Dense Grid Based Object Detection
2020
Object detection is one of the most challenging and very important branch of computer vision. Some of the challenging aspect of a detection network is the fact that an object can appear anywhere in the image, be partially occluded by another object, might appear in crowd or have greatly varying scales. Consequently, we propose a fine grained and equally spaced dense grid cells throughout an input image be responsible of detecting an object. We re-purpose an already existing deep state-of-the-art detector or classifier into deep and dense detector. Our dense object detector uses binary class encoding and hence suitable for very large multi-class object detector. We also propose a more flexib…
Features extraction on complex images
2005
The accessibility of inexpensive and powerful computers has allowed true digital holography to be used for industrial inspection using microscopy. This technique allows the capture of a complex image (i.e., one containing magnitude and phase), and the reconstruction of the phase and magnitude information. Digital holograms give a new dimension to texture analysis, since the topology information can be used as an additional way to extract features. This new technique can be used to extend previous work on the image segmentation of patterned wafers for defect detection. The paper presents a comparison between the features obtained using Gabor filtering on complex images under illumination and…