50 research outputs found

    ADAPTABLE FINGERPRINT MINUTIAE EXTRACTION ALGORITHM BASED-ON CROSSING NUMBER METHOD FOR HARDWARE IMPLEMENTATION USING FPGA DEVICE

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    In this article. a main perspective of developing and implementing fingerprint extraction and matching algorithms as a pari of fingerprint recognition system is focused. First, developing a simple algorithm to extract fingerprint features and test this algorithm on Pc. The second thing is implementing this algorithm into FPGA devices. The major research topics on which the proposed approach is developing and modifying fingerprint extraction feature algorithm. This development and modification are using crossing number method on pixel representation value '0'. In this new proposed algorithm, it is no need a process concerning ROI segmentation and no trigonometry calculation. And specially in obtaining their parameters using Angle Calculation Block avoiding floating points calculation. As this method is local feature that usually involve with 60-100 minutiae points, makes the template is small in size. Providing FAR. FRR and EER, performs the performance evaluation of proposed algorithm. The result is an adaptable fingerprint minutiae extraction algorithm into hardware implementation with 14.05 % of EEl?, better than reference algorithm, which is 20.39 % . The computational time is 18 seconds less than a similar method, which takes 60-90 seconds just for pre-processing step. The first step of algorithm implementation in hardware environment (embedded) using FPGA Device by developing IP Core without using any soft processor is presented

    Field programmable gate arrays-based number plate binarization and adjustment for automatic number plate recognition systems

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    Copyright 2013 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibitedNumber Plate (NP) binarisation and adjustment are very important pre-processing stages in Automatic Number Plate Recognition (ANPR) systems and are used to link the Number Plate Localisation (NPL) and Character segmentation (CS) stages. Successfully linking these two stages will improve the performance of the entire ANPR system. This paper presents two optimised low complexity NP binarisation and adjustment algorithms. Efficient area/speed architectures based on the proposed algorithms are also presented and have been successfully implemented and tested using the Mentor Graphics RC240 FPGA development board, which together require only 9% of the available on-chip resources of a Virtex-4 FPGA, run with a maximum frequency of 95.8 MHz and are capable of processing one image in 0.07-0.17ms.Peer reviewedFinal Accepted Versio

    Sensors and Technologies in Spain: State-of-the-Art

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    The aim of this special issue was to provide a comprehensive view on the state-of-the-art sensor technology in Spain. Different problems cause the appearance and development of new sensor technologies and vice versa, the emergence of new sensors facilitates the solution of existing real problems. [...

    Advanced Image Acquisition, Processing Techniques and Applications

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    "Advanced Image Acquisition, Processing Techniques and Applications" is the first book of a series that provides image processing principles and practical software implementation on a broad range of applications. The book integrates material from leading researchers on Applied Digital Image Acquisition and Processing. An important feature of the book is its emphasis on software tools and scientific computing in order to enhance results and arrive at problem solution

    Vision-based Detection of Mobile Device Use While Driving

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    The aim of this study was to explore the feasibility of an automatic vision-based solution to detect drivers using mobile devices while operating their vehicles. The proposed system comprises of modules for vehicle license plate localisation, driver’s face detection and mobile phone interaction. The system were then implemented and systematically evaluated using suitable image datasets. The strengths and weaknesses of individual modules were analysed and further recommendations made to improve the overall system’s performance

    Embedded electronic systems driven by run-time reconfigurable hardware

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    Abstract This doctoral thesis addresses the design of embedded electronic systems based on run-time reconfigurable hardware technology –available through SRAM-based FPGA/SoC devices– aimed at contributing to enhance the life quality of the human beings. This work does research on the conception of the system architecture and the reconfiguration engine that provides to the FPGA the capability of dynamic partial reconfiguration in order to synthesize, by means of hardware/software co-design, a given application partitioned in processing tasks which are multiplexed in time and space, optimizing thus its physical implementation –silicon area, processing time, complexity, flexibility, functional density, cost and power consumption– in comparison with other alternatives based on static hardware (MCU, DSP, GPU, ASSP, ASIC, etc.). The design flow of such technology is evaluated through the prototyping of several engineering applications (control systems, mathematical coprocessors, complex image processors, etc.), showing a high enough level of maturity for its exploitation in the industry.Resumen Esta tesis doctoral abarca el diseño de sistemas electrónicos embebidos basados en tecnología hardware dinámicamente reconfigurable –disponible a través de dispositivos lógicos programables SRAM FPGA/SoC– que contribuyan a la mejora de la calidad de vida de la sociedad. Se investiga la arquitectura del sistema y del motor de reconfiguración que proporcione a la FPGA la capacidad de reconfiguración dinámica parcial de sus recursos programables, con objeto de sintetizar, mediante codiseño hardware/software, una determinada aplicación particionada en tareas multiplexadas en tiempo y en espacio, optimizando así su implementación física –área de silicio, tiempo de procesado, complejidad, flexibilidad, densidad funcional, coste y potencia disipada– comparada con otras alternativas basadas en hardware estático (MCU, DSP, GPU, ASSP, ASIC, etc.). Se evalúa el flujo de diseño de dicha tecnología a través del prototipado de varias aplicaciones de ingeniería (sistemas de control, coprocesadores aritméticos, procesadores de imagen, etc.), evidenciando un nivel de madurez viable ya para su explotación en la industria.Resum Aquesta tesi doctoral està orientada al disseny de sistemes electrònics empotrats basats en tecnologia hardware dinàmicament reconfigurable –disponible mitjançant dispositius lògics programables SRAM FPGA/SoC– que contribueixin a la millora de la qualitat de vida de la societat. S’investiga l’arquitectura del sistema i del motor de reconfiguració que proporcioni a la FPGA la capacitat de reconfiguració dinàmica parcial dels seus recursos programables, amb l’objectiu de sintetitzar, mitjançant codisseny hardware/software, una determinada aplicació particionada en tasques multiplexades en temps i en espai, optimizant així la seva implementació física –àrea de silici, temps de processat, complexitat, flexibilitat, densitat funcional, cost i potència dissipada– comparada amb altres alternatives basades en hardware estàtic (MCU, DSP, GPU, ASSP, ASIC, etc.). S’evalúa el fluxe de disseny d’aquesta tecnologia a través del prototipat de varies aplicacions d’enginyeria (sistemes de control, coprocessadors aritmètics, processadors d’imatge, etc.), demostrant un nivell de maduresa viable ja per a la seva explotació a la indústria

    Low Power Memory/Memristor Devices and Systems

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    This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within

    Diseño CMOS de un sistema de visión “on-chip” para aplicaciones de muy alta velocidad

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    Falta palabras claveEsta Tesis presenta arquitecturas, circuitos y chips para el diseño de sensores de visión CMOS con procesamiento paralelo embebido. La Tesis reporta dos chips, en concreto: El chip Q-Eye; El chip Eye-RIS_VSoC.. Y dos sistemas de visión construidos con estos chips y otros sistemas “off-chip” adicionales, como FPGAs, en concreto: El sistema Eye-RIS_v1; El sistema Eye-RIS_v2. Estos chips y sistemas están concebidos para ejecutar tareas de visión a muy alta velocidad y con consumos de potencia moderados. Los sistemas resultantes son, además, compactos y por lo tanto ventajosos en términos del factor SWaP cuando se los compara con arquitecturas convencionales formadas por sensores de imágenes convencionales seguidos de procesadores digitales. La clave de estas ventajas en términos de SWaP y velocidad radica en el uso de sensores-procesadores, en lugar de meros sensores, en la interface de los sistemas de visión. Estos sensores-procesadores embeben procesadores programables de señal-mixta dentro del pixel y son capaces tanto de adquirir imágenes como de pre-procesarlas para extraer características, eliminar información redundante y reducir el número de datos que se transmiten fuera del sensor para su procesamiento ulterior. El núcleo de la tesis es el sensor-procesador Q-Eye, que se usa como interface en los sistemas Eye-RIS. Este sensor-procesador embebe una arquitectura de procesamiento formada por procesadores de señal-mixta distribuidos por pixel. Sus píxeles son por tanto estructuras multi-funcionales complejas. De hecho, son programables, incorporan memorias e interactúan con sus vecinos para realizar una variedad de operaciones, tales como: Convoluciones lineales con máscaras programables; Difusiones controladas por tiempo y nivel de señal, a través de un “grid” resistivo embebido en el plano focal; Aritmética de imágenes; Flujo de programación dependiente de la señal; Conversión entre los dominios de datos: imagen en escala de grises e imagen binaria; Operaciones lógicas en imágenes binarias; Operaciones morfológicas en imágenes binarias. etc. Con respecto a otros píxeles multi-función y sensores-procesadores anteriores, el Q-Eye reporta entre otras las siguientes ventajas: Mayor calidad de la imagen y mejores prestaciones de las funcionalidades embebidas en el chip; Mayor velocidad de operación y mejor gestión de la energía disponible; Mayor versatilidad para integración en sistemas de visión industrial. De hecho, los sistemas Eye-RIS son los primeros sistemas de visión industriales dotados de las siguientes características: Procesamiento paralelo distribuido y progresivo; Procesadores de señal-mixta fiables, robustos y con errores controlados; Programabilidad distribuida. La Tesis incluye descripciones detalladas de la arquitectura y los circuitos usados en el pixel del Q-Eye, del propio chip Q-Eye y de los sistemas de visión construidos en base a este chip. Se incluyen también ejemplos de los distintos chips en operaciónThis Thesis presents architectures, circuits and chips for the implementation of CMOS VISION SENSORS with embedded parallel processing. The Thesis reports two chips, namely: Q-eye chip; Eye-RIS_VSoC chip, and two vision systems realized by using these chips and some additional “off-chip” circuitry, such as FPGAs. These vision systems are: Eye-RIS_v1 system; Eye-RIS_v2 system. The chips and systems reported in the Thesis are conceived to perform vision tasks at very high speed and with moderate power consumption. The proposed vision systems are also compact and advantageous in terms of SWaP factors as compared with conventional architectures consisting of standard image sensor followed by digital processors. The key of these advantages in terms of SWaP and speed lies in the use of sensors-processors, rather than mere sensors, in the front-end interface of vision systems. These sensors-processors embed mixed-signal programmable processors inside the pixel. Therefore, they are able to acquire images and process them to extract the features, removing the redundant information and reducing the data throughput for later processing. The core of the Thesis is the sensor-processor Q-Eye, which is used as front-end in the Eye-RIS systems. This sensor-processor embeds a processing architecture composed by mixed-signal processors distributed per pixel. Then, its pixels are complex multi-functional structures. In fact, they are programmable, incorporate memories and interact with its neighbors in order to carry out a set of operations, including: Linear convolutions with programmable linear masks; Time- and signal-controlled diffusions (by means of an embedded resistive grid); Image arithmetic; Signal-dependent data scheduling; Gray-scale to binary transformation; Logic operation on binary images; Mathematical morphology on binary images, etc. As compared with previous multi-function pixels and sensors-processors, the Q-Eye brings among other the following advantages: Higher image quality and better performances of functionalities embedded on chip; Higher operation speed and better management of energy budget; More versatility for integration in industrial vision systems. In fact, the Eye-RIS systems are the first industrial vision systems equipped with the following characteristics: Parallel distributed and progressive processing; Reliable, robust mixed-signal processors with handled errors; Distributed programmability. This Thesis includes detailed descriptions of architecture and circuits used in the Q-Eye pixel, in the Q-Eye chip itself and in the vision systems developed based on this chip. Also, several examples of chips and systems in operation are presented
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