47 research outputs found
Change Detection and Non Stationary Signals Tracking by Adaptive Filtering
In this paper we consider the problem of change
detection and non stationary signals tracking. Using parametric
estimation of signals based on least square lattice adaptive filters we
consider for change detection statistical parametric methods using
likelihood ratio and hypothesis tests. In order to track signals
dynamics, we introduce a compensation procedure in the adaptive
estimation. This will improve the adaptive estimation performances
and fasten it-s convergence after changes detection
Change detection and non stationary signals tracking by adaptive filtering
ABSTRACT In this paper we consider the problem of change detection and non stationary signals tracking. Using parametric estimation of signals based on least square lattice adaptive filters we consider for change detection statistical parametric methods using likelihood ratio and hypothesis tests. In order to track signals dynamics, we introduce a compensation procedure in the adaptive estimation. This will improve the adaptive estimation performances and fasten it's convergence after changes detectio
Proposing a new evaluation metric to improved view random access for multi-view video coding
Change detection and non stationary signals tracking by adaptive filtering
ABSTRACT In this paper we consider the problem of change detection and non stationary signals tracking. Using parametric estimation of signals based on least square lattice adaptive filters we consider for change detection statistical parametric methods using likelihood ratio and hypothesis tests. In order to track signals dynamics, we introduce a compensation procedure in the adaptive estimation. This will improve the adaptive estimation performances and fasten it's convergence after changes detectio
Contribution to the video transmission improvement in vehicular ad-hoc networks (VANETs)
Actuellement les communications véhiculaires sont devenues une réalité guidée par diverses applications. Notamment, la diffusion de vidéo de qualité élevée avec des contraintes de faible latence requises par les applications temps réel. Grâce au niveau de compression jamais atteint auparavant, l’encodeur H.265/HEVC est très prometteur pour la diffusion de vidéos en temps réel dans les réseaux ad hoc véhiculaire (VANET). Néanmoins, la qualité de la vidéo reçue est pénalisée par les mauvaises caractéristiques du canal de transmission (disponibilité, non stationnarité, rapport signal à bruit, etc.). Afin d’améliorer et d’assurer une qualité vidéo minimale à la réception nous proposons dans ce travail une optimisation conjointe source-canal-protocole de la transmission en tenant compte à la fois des paramètres de transmission et d’encodage vidéo. Dans un premier temps, nous montrons l’intérêt et le gain apporté par les solutions dites inter-couches « cross-layer ». Par la suite, nous développons deux approches l’une exploitant un « cross-layer » entre la couche application et la couche MAC et une seconde exploitant les protocoles de transports dans l’adaptation du flux vidéo. En ce qui concerne la première approche nous proposons une solution utilisant une gestion hiérarchique des trames au niveau des files d’attentes de la couche MAC, basée sur l’importance des images du flux vidéo. Dans une seconde solution, nous retenons le codage par descriptions multiples comme solution de protection à la source. Les résultats de simulations obtenus pour plusieurs types de scénarios véhiculaires réalistes montrent que les différents schémas de transmission véhiculaire proposés offrent des améliorations significatives en termes de qualité vidéo à la réception et de retard de bout en bout par rapport aux schémas classiques.At present, vehicular communications have become a reality guided by various applications. In particular, high-quality video delivery with low latency constraints is required for real-time applications. The new state-of-the-art high-effciency video coding (HEVC) standard is very promising for real-time video streaming in vehicular ad hoc networks (VANET). Nevertheless, these networks have variable channel quality and a limited bandwidth that penalizes the overall performances of end-to-end video transmission. In order to meet these constraints, we proposed in this work to consider both transmission and video encoding parameters through a joint source-channel-protocol coding approach to provide an improvement in video transmission. First, we have shown the interest and the gain brought by the "cross-layer" solutions. Then, we developed two approaches. The first one exploits a "crosslayer" solution between the application layer and the Medium Access Control (MAC) layer while the second exploits the transport layer protocols in the adaptation of the video stream. Regarding the first approach, we have proposed solutions to allocate the frames to the most appropriate Access Category (AC) queue on the MAC layer based on the image importance in the video stream. In another solution, we chose multiple descriptions source coding as an error resilient solution. Thus, the simluation results obtained for different realistic vehicular scenarios demonstrate that the proposed transmission schemes offer significant video quality improvements and end-to-end delay reduction compared to conventional transmission schemes
An efficient palmprint biometric system based on progressive image compression
International audienceIn this paper, we propose an efficient multi-spectral palmprint identification system. For that, we compressed each palmprint band at 0.5 bit per pixel (bpp) by a progressive image compression algorithm where we used the famous Set Partitioning In Hierarchical Trees (SPIHT ) coder. By exploiting the progressiveness of this algorithm, we obtained three images decompressed in several times with different resolutions. One image decompressed at 0.25 bpp which represents the image approximation, the other at 0.25 bpp which represents the edges or details and the third is the global of them. So, we applied a binarization scheme and the Gabor algorithm for the last two images respectively for modeling. Subsequently, all bands are integrated in order to construct an efficient multimodal identification system based on matching score level fusion. Finally, Experimental results show that our proposed scheme yields excellent performance for identifying palmprint
Telehealth care enhancement using the internet of things technology
Chronic diseases quickly become broader public health issues because of the difficulty in obtaining appropriate, often long-term health care. So that, it requires the extension of health care for patients with chronic diseases beyond the clinic to include patient’s home and work environment. To reduce costs and provide more appropriate healthcare, we need telehealth care where internet of things (IoT) technology plays an important role. The integration of the IoT and medical science offers opportunities to improve healthcare quality, and efficiency and to better coordinate healthcare delivery at home and in the workplace. In this paper, we present the realization of a remote healthcare system based on the IoT technology. The function of this system is the transmission via a gateway of internet collected data using biomedical sensors node based Arduino board (e.g., temperature, electrical activity of the heart, heart rate monitor). These data will be stored automatically in a cloud. The health can then be monitored by the doctor or patient using a web page in real-time from anywhere at any time in the world using laptops or smart phones, etc. This method also reduces the need for direct interaction between doctor and patient
