Search results for "FILTER"
showing 10 items of 1019 documents
Lau Effect And Binary Logic
1989
The Lau effect is applied to implement the whole set of binary logic operations optically. Our technique works with spatially incoherent light and does not require lenses or any other optical accessory.
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…
<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…
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 …
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…
Target tracking with dynamically adaptive correlation
2016
Abstract A reliable algorithm for target tracking based on dynamically adaptive correlation filtering is presented. The algorithm is capable of tracking with high accuracy the location of a target in an input video sequence without using an offline training process. The target is selected at the beginning of the algorithm. Afterwards, a composite correlation filter optimized for distortion tolerant pattern recognition is designed to recognize the target in the next frame. The filter is dynamically adapted to each frame using information of current and past scene observations. Results obtained with the proposed algorithm in synthetic and real-life video sequences, are analyzed and compared w…
SmartSpectra: Applying multispectral imaging to industrial environments
2005
SmartSpectra is a smart multispectral system for industrial, environmental, and commercial applications where the use of spectral information beyond the visible range is needed. The SmartSpectra system provides six spectral bands in the range 400-1000nm. The bands are configurable in terms of central wavelength and bandwidth by using electronic tunable filters. SmartSpectra consists of a multispectral sensor and the software that controls the system and simplifies the acquisition process. A first prototype called Autonomous Tunable Filter System is already available. This paper describes the SmartSpectra system, demonstrates its performance in the estimation of chlorophyll in plant leaves, …
A Hybrid Algorithm Based on WiFi for Robust and Effective Indoor Positioning
2019
Indoor positioning based on the Wireless Fidelity (WiFi) protocol and the Pedestrian Dead Reckoning (PDR) approach is widely exploited because of the existing WiFi infrastructure in buildings and the advancement of built-in smartphone sensors. In this work, a hybrid algorithm that combines WiFi fingerprinting and PDR to both exploit their advantages as well as limiting the impact of their disadvantages is proposed. Specifically, to build a probability map from noisy Received Signal Strength (RSS), a Gaussian Process (GP) regression is deployed to estimate and construct the RSS fingerprints with incomplete data. Mean and variance of generated points are used to estimate WiFi fingerprinting p…
A Sentiment Enhanced Deep Collaborative Filtering Recommender System
2021
Recommender systems use advanced analytic and learning techniques to select relevant information from massive data and inform users’ smart decision-making on their daily needs. Numerous works exploiting user’s sentiments on products to enhance recommendations have been introduced. However, there has been relatively less work exploring higher-order user-item features interactions for sentiment enhanced recommender system. In this paper, a novel Sentiment Enhanced Deep Collaborative Filtering Recommender System (SE-DCF) is developed. The architecture is based on a Neural Attention network component aggregated with the output predictions of a Convolution Neural Network (CNN) recommender. Speci…