5 research outputs found

    Image Sensors in Security and Medical Applications

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    This paper briefly reviews CMOS image sensor technology and its utilization in security and medical applications. The role and future trends of image sensors in each of the applications are discussed. To provide the reader deeper understanding of the technology aspects the paper concentrates on the selected applications such as surveillance, biometrics, capsule endoscopy and artificial retina. The reasons for concentrating on these applications are due to their importance in our daily life and because they present leading-edge applications for imaging systems research and development. In addition, review of image sensors implementation in these applications allows the reader to investigate image sensor technology from the technical and from other views as well

    Compressive Image Acquisition in Modern CMOS IC Design

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    Compressive Sampling (CS) offers bandwidth, power and memory size reduction compared to conventional (Nyquist) sampling. However, very few Integrated Circuit (IC) designs based on CS exist due to the missing link between the well-established CS theory on one side, and the practical aspects/effects related to physical IC design on the other side. This paper focuses on the application of compressed image acquisition in CMOS image sensor integrated circuit design. A new CS scheme is proposed which is suited for hardware implementation in CMOS IC design. All the main physical non-idealities are explained and carefully modeled. Their influences on the acquired image quality are analyzed in the general case and quantifed for the case of the proposed CS scheme. The presented methodology can also be used for different CS schemes and as a general guideline in future CS based CMOS image sensor designs

    Foveated Sampling Architectures for CMOS Image Sensors

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    Electronic imaging technologies are faced with the challenge of power consumption when transmitting large amounts of image data from the acquisition imager to the display or processing devices. This is especially a concern for portable applications, and becomes more prominent in increasingly high-resolution, high-frame rate imagers. Therefore, new sampling techniques are needed to minimize transmitted data, while maximizing the conveyed image information. From this point of view, two approaches have been proposed and implemented in this thesis: A system-level approach, in which the classical 1D row sampling CMOS imager is modified to a 2D ring sampling pyramidal architecture, using the same standard three transistor (3T) active pixel sensor (APS). A device-level approach, in which the classical orthogonal architecture has been preserved while altering the APS device structure, to design an expandable multiresolution image sensor. A new scanning scheme has been suggested for the pyramidal image sensor, resulting in an intrascene foveated dynamic range (FDR) similar in profile to that of the human eye. In this scheme, the inner rings of the imager have a higher dynamic range than the outer rings. The pyramidal imager transmits the sampled image through 8 parallel output channels, allowing higher frame rates. The human eye is known to have less sensitivity to oblique contrast. Using this fact on the typical oblique distribution of fixed pattern noise, we demonstrate lower perception of this noise than the orthogonal FPN distribution of classical CMOS imagers. The multiresolution image sensor principle is based on averaging regions of low interest from frame-sampled image kernels. One pixel is read from each kernel while keeping pixels in the region of interest at their high resolution. This significantly reduces the transferred data and increases the frame rate. Such architecture allows for programmability and expandability of multiresolution imaging applications

    Conception d'un micro capteur d'image CMOS à faible consommation d'énergie pour les réseaux de capteurs sans fil

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    This research aims to develop a vision system with low energy consumption for Wireless Sensor Networks (WSNs). The imager in question must meet the specific requirements of multimedia applications for Wireless Vision Sensor Networks. Indeed, a multimedia application requires intensive computation at the node and a considerable number of packets to be exchanged through the transceiver, and therefore consumes a lot of energy. An obvious solution to reduce the amount of transmitted data is to compress the images before sending them over WSN nodes. However, the severe constraints of nodes make ineffective in practice the implementation of standard compression algorithms (JPEG, JPEG2000, MJPEG, MPEG, H264, etc.). Desired vision system must integrate image compression techniques that are both effective and with low-complexity. Particular attention should be taken into consideration in order to best satisfy the compromise "Energy Consumption - Quality of Service (QoS)".Ce travail de recherche vise à concevoir un système de vision à faible consommation d'énergie pour les réseaux de capteurs sans fil. L'imageur en question doit respecter les contraintes spécifiques des applications multimédias pour les réseaux de capteurs de vision sans fil. En effet, de par sa nature, une application multimédia impose un traitement intensif au niveau du noeud et un nombre considérable de paquets à échanger à travers le lien radio, et par conséquent beaucoup d'énergie à consommer. Une solution évidente pour diminuer la quantité de données transmise, et donc la durée de vie du réseau, est de compresser les images avant de les transmettre. Néanmoins, les contraintes strictes des noeuds du réseau rendent inefficace en pratique l'exécution des algorithmes de compression standards (JPEG, JPEG2000, MJPEG, MPEG, H264, etc.). Le système de vision à concevoir doit donc intégrer des techniques de compression d'image à la fois efficaces et à faible complexité. Une attention particulière doit être prise en compte en vue de satisfaire au mieux le compromis "Consommation énergétique - Qualité de Service (QoS)"
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