Search results for "image processing"
showing 10 items of 3285 documents
Motion analysis using the novelty filter
1991
Abstract An original approach to the motion analysis, based on the novelty filter, is proposed. The novelty filter stresses the novelties occurring in a pattern representing an image of the scene under consideration with respect to patterns representing previous images of the same scene, so that visual information about the motion of the objects is obtained. The novelty filter may be implemented by a neural network architecture, taking advantage of the capabilities of massive parallelism, adaptive learning and noise robustness. The novelty filter may learn the entire trajectory of an object, through an incremental learning of a sequence of images capturing the scene, thus emphasizing if the…
Selective Change Driven Imaging: A Biomimetic Visual Sensing Strategy
2011
Selective Change Driven (SCD) Vision is a biologically inspired strategy for acquiring, transmitting and processing images that significantly speeds up image sensing. SCD vision is based on a new CMOS image sensor which delivers, ordered by the absolute magnitude of its change, the pixels that have changed after the last time they were read out. Moreover, the traditional full frame processing hardware and programming methodology has to be changed, as a part of this biomimetic approach, to a new processing paradigm based on pixel processing in a data flow manner, instead of full frame image processing.
Hardware Implementation of a Configurable Motion Estimator for Adjusting the Video Coding Performances
2012
International audience; Despite the diversity of video compression standard, the motion estimation still remains a key process which is used in most of them. Moreover, the required coding performances (bit-rate, PSNR, image spatial resolution, etc.) depend obviously of the application, the environment and the network communication. The motion estimation can therefore be adapted to fit with these performances. Meanwhile, the real time encoding is required in many applications. In order to reach this goal, we propose in this paper a hardware implementation of the motion estimator which enables the integer motion search algorithms to be modified and the fractional search and variable block siz…
A genetic algorithm for scratch removal in static images
2002
This paper investigates the removal of line scratches from old moving pictures and gives a twofold contribution. First, it presents a simple technique for detecting the scratches, based on an analysis of the statistics of the grey levels. Second, the scratch removal is approached as an optimisation problem, which is solved by using a genetic algorithm. The method can be classified as a static approach, as it works independently on each single frame of the sequence. It does not require any a-priori knowledge of the absolute position of the scratch, nor an external starting population of chromosomes for the genetic algorithm. The central column of the line scratch once detected is changed wit…
Study of fibrosis induced by an implanted medical device
2014
National audience; This paper focuses on the study of fibrosis induced by an implanted medical device and explores the possibility of characterizing this process by in situ measurement of electrical impedance. The approach combines electrical and biological characterizations of fibrotic tissue, applied to electrodes implanted in animal models. A comparative study of electrical and biological parameters collected at the same time will enable the identification of an electrical marker of fibrosis development, which can be used for establishing a monitoring method. Adopting an interdisciplinary approach, intermediate embedded prototypes, autonomous and portable by animals, will be developed to…
Multi-focus image fusion using local variability
2018
In this thesis, we are interested in the multi-focus image fusion method. This technique consists of fusing several captured images with different focal lengths of the same scene to obtain an image with better quality than the two source images. We propose an image fusion method based on Laplacian pyramid technique using Discrete Wavelet Transform (DWT) as a selection rule. We then develop two multi-focus image fusion methods based on the local variability of each pixel. It takes into account the information in the surrounding pixel area. The first method is to use local variability as an information in the Dempster-Shafer theory. The second method uses a metric based on local variability. …
Depth Attention for Scene Understanding
2022
Deep learning models can nowadays teach a machine to realize a number of tasks, even with better precision than human beings. Among all the modules of an intelligent machine, perception is the most essential part without which all other action modules have difficulties in safely and precisely realizing the target task under complex scenes. Conventional perception systems are based on RGB images which provide rich texture information about the 3D scene. However, the quality of RGB images highly depends on environmental factors, which further influence the performance of deep learning models. Therefore, in this thesis, we aim to improve the performance and robustness of RGB models with comple…
Analyse et fusion d’images multimodales pour la navigation autonome
2021
Robust semantic scene understanding is challenging due to complex object types, as well as environmental changes caused by varying illumination and weather conditions. This thesis studies the problem of deep semantic segmentation with multimodal image inputs. Multimodal images captured from various sensory modalities provide complementary information for complete scene understanding. We provided effective solutions for fully-supervised multimodal image segmentation and few-shot semantic segmentation of the outdoor road scene. Regarding the former case, we proposed a multi-level fusion network to integrate RGB and polarimetric images. A central fusion framework was also introduced to adaptiv…
Suffix Array Construction on Multi-GPU Systems
2019
Suffix arrays are prevalent data structures being fundamental to a wide range of applications including bioinformatics, data compression, and information retrieval. Therefore, various algorithms for (parallel) suffix array construction both on CPUs and GPUs have been proposed over the years. Although providing significant speedup over their CPU-based counterparts, existing GPU implementations share a common disadvantage: input text sizes are limited by the scarce memory of a single GPU. In this paper, we overcome aforementioned memory limitations by exploiting multi-GPU nodes featuring fast NVLink interconnects. In order to achieve high performance for this communication-intensive task, we …
Design and Implementation of a Low-cost Embedded Iris Recognition System on a Dual-core Processor Platform
2012
Abstract Design of a low-cost embedded iris recognition system is described in this paper. Firstly, we develop a simple and effective iris image acquisition unit, which is cheap and easy to use. This is achieved by both of hardware design and image evaluation algorithm development. Secondly, the iris recognition algorithm is introduced, including iris segmentation, image normalization, feature extraction, and code matching. The algorithm implementation architecture is based on an embedded dual-core processor platform, Texas Instruments TMS320DM6446 evaluation module (Davinci), which contains an ARM core and a DSP core in one chip. Thirdly, the evaluation experiments are performed on the est…