Méthode de conception de l'architecture d'un capteur de vision dédié au contrôle qualité

Aujourd'hui l'optique et l'électronique modernes permettent d'envisager l'intégration sur un même circuit des capteurs pour l'acquisition et des processeurs pour le traitement d'images. De tels dispositifs constituent un élément essentiel des recherches actuelles sur les capteurs de vision. Notre but est de concevoir et de valider une méthodologie pour l'adéquation entre algorithme de traitements d'images et architectures de capteur et de processeur de traitement. L'optimisation recherchée tout au long de notre étude vise à réaliser l'architecture de traitement juste nécessaire aux besoins de l'algorithme de traitements d'images

自己投影法に基づく高速三次元形状検査の研究

広島大学(Hiroshima University)博士(工学)Doctor of Engineeringdoctora

高速ビジョンを用いた振動源定位に関する研究

広島大学(Hiroshima University)博士(工学)Doctor of Engineeringdoctora

New Views for Stochastic Computing: From Time-Encoding to Deterministic Processing

University of Minnesota Ph.D. dissertation.July 2018. Major: Electrical/Computer Engineering. Advisor: David Lilja. 1 computer file (PDF); xi, 149 pages.Stochastic computing (SC), a paradigm first introduced in the 1960s, has received considerable attention in recent years as a potential paradigm for emerging technologies and ''post-CMOS'' computing. Logical computation is performed on random bitstreams where the signal value is encoded by the probability of obtaining a one versus a zero. This unconventional representation of data offers some intriguing advantages over conventional weighted binary. Implementing complex functions with simple hardware (e.g., multiplication using a single AND gate), tolerating soft errors (i.e., bit flips), and progressive precision are the primary advantages of SC. The obvious disadvantage, however, is latency. A stochastic representation is exponentially longer than conventional binary radix. Long latencies translate into high energy consumption, often higher than that of their binary counterpart. Generating bit streams is also costly. Factoring in the cost of the bit-stream generators, the overall hardware cost of an SC implementation is often comparable to a conventional binary implementation. This dissertation begins by proposing a highly unorthodox idea: performing computation with digital constructs on time-encoded analog signals. We introduce a new, energy-efficient, high-performance, and much less costly approach for SC using time-encoded pulse signals. We explore the design and implementation of arithmetic operations on time-encoded data and discuss the advantages, challenges, and potential applications. Experimental results on image processing applications show up to 99% performance speedup, 98% saving in energy dissipation, and 40% area reduction compared to prior stochastic implementations. We further introduce a low-cost approach for synthesizing sorting network circuits based on deterministic unary bit-streams. Synthesis results show more than 90% area and power savings compared to the costs of the conventional binary implementation. Time-based encoding of data is then exploited for fast and energy-efficient processing of data with the developed sorting circuits. Poor progressive precision is the main challenge with the recently developed deterministic methods of SC. We propose a high-quality down-sampling method which significantly improves the processing time and the energy consumption of these deterministic methods by pseudo-randomizing bitstreams. We also propose two novel deterministic methods of processing bitstreams by using low-discrepancy sequences. We further introduce a new advantage to SC paradigm-the skew tolerance of SC circuits. We exploit this advantage in developing polysynchronous clocking, a design strategy for optimizing the clock distribution network of SC systems. Finally, as the first study of its kind to the best of our knowledge, we rethink the memory system design for SC. We propose a seamless stochastic system, StochMem, which features analog memory to trade the energy and area overhead of data conversion for computation accuracy

Smart vision in system-on-chip applications

In the last decade the ability to design and manufacture integrated circuits with higher transistor densities has led to the integration of complete systems on a single silicon die. These are commonly referred to as System-on-Chip (SoC). As SoCs processes can incorporate multiple technologies it is now feasible to produce single chip camera systems with embedded image processing, known as Imager-on-Chips (IoC). The development of IoCs is complicated due to the mixture of digital and analog components and the high cost of prototyping these designs using silicon processes. There are currently no re-usable prototyping platforms that specifically address the needs of IoC development. This thesis details a new prototyping platform specifically for use in the development of low-cost mass-market IoC applications. FPGA technology was utilised to implement a frame-based processing architecture suitable for supporting a range of real-time imaging and machine vision applications. To demonstrate the effectiveness of the prototyping platform, an example object counting and highlighting application was developed and functionally verified in real-time. A high-level IoC cost model was formulated to calculate the cost of manufacturing prototyped applications as a single IoC. This highlighted the requirement for careful analysis of optical issues, embedded imager array size and the silicon process used to ensure the desired IoC unit cost was achieved. A modified version of the FPGA architecture, which would result in improving the DSP performance, is also proposed

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

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