Programmable retinal dynamics in a CMOS mixed-signal array processor chip

The low-level image processing that takes place in the retina is intended to compress the relevant visual information to a manageable size. The behavior of the external layers of the biological retina has been successfully modelled by a Cellular Neural Network, whose evolution can be described by a set of coupled nonlinear differential equations. A mixed-signal VLSI implementation of the focal-plane low-level image processing based upon this biological model constitutes a feasible and cost effective alternative to conventional digital processing in real-time applications. For these reasons, a programmable array processor prototype chip has been designed and fabricated in a standard 0.5μm CMOS technology. The integrated system consists of a network of two coupled layers, containing 32 × 32 elementary processors, running at different time constants. Involved image processing algorithms can be programmed on this chip by tuning the appropriate interconnections weights. Propagative, active wave phenomena and retina-like effects can be observed in this chip. Design challenges, trade-offs, the buildings blocks and some test results are presented in this paper.Office of Naval Research (USA) N00014-00-10429European Community IST-1999-19007Ministerio de Ciencia y Tecnología TIC1999-082

A versatile sensor interface for programmable vision systems-on-chip

This paper describes an optical sensor interface designed for a programmable mixed-signal vision chip. This chip has been designed and manufactured in a standard 0.35μm n-well CMOS technology with one poly layer and five metal layers. It contains a digital shell for control and data interchange, and a central array of 128 × 128 identical cells, each cell corresponding to a pixel. Die size is 11.885 × 12.230mm2 and cell size is 75.7μm × 73.3μm. Each cell contains 198 transistors dedicated to functions like processing, storage, and sensing. The system is oriented to real-time, single-chip image acquisition and processing. Since each pixel performs the basic functions of sensing, processing and storage, data transferences are fully parallel (image-wide). The programmability of the processing functions enables the realization of complex image processing functions based on the sequential application of simpler operations. This paper provides a general overview of the system architecture and functionality, with special emphasis on the optical interface.European Commission IST-1999-19007Office of Naval Research (USA) N00014021088

ACE 16k based stand-alone system for real-time pre-processing tasks

This paper describes the design of a programmable stand-alone system for real time vision pre-processing tasks. The system's architecture has been implemented and tested using an ACE16k chip and a Xilinx xc4028xl FPGA. The ACE16k chip consists basically of an array of 128×128 identical mixed-signal processing units, locally interacting, which operate in accordance with single instruction multiple data (SIMD) computing architectures and has been designed for high speed image pre-processing tasks requiring moderate accuracy levels (7 bits). The input images are acquired using the optical input capabilities of the ACE16k chip, and after being processed according to a programmed algorithm, the images are represented at real time on a TFT screen. The system is designed to store and run different algorithms and to allow changes and improvements. Its main board includes a digital core, implemented on a Xilinx 4028 Series FPGA, which comprises a custom programmable Control Unit, a digital monochrome PAL video generator and an image memory selector. Video SRAM chips are included to store and access images processed by the ACE16k. Two daughter boards hold the program SRAM and a video DAC-mixer card is used to generate composite analog video signal.European Commission IST2001 – 38097Ministerio de Ciencia y Tecnología TIC2003 – 09817- C02 – 01Office of Naval Research (USA) N00014021088

Tactile on-chip pre-processing with techniques from artificial retinas

The interest in tactile sensors is increasing as their use in complex unstructured environments is demanded, like in tele-presence, minimal invasive surgery, robotics etc. The matrix of pressure data these devices provide can be managed with many image processing algorithms to extract the required information. However, as in the case of vision chips or artificial retinas, problems arise when the array size and the computation complexity increase. Having a look to the skin, the information collected by every mechanoreceptor is not carried to the brain for its processing, but some complex pre-processing is performed to fit the limited throughput of the nervous system. This is specially important for high bandwidth demanding tasks. Experimental works report that neural response of skin mechanoreceptors encodes the change in local shape from an offset level rather than the absolute force or pressure distributions. This is also the behavior of the retina, which implements a spatio-temporal averaging. We propose the same strategy in tactile preprocessing, and we show preliminary results when it faces the detection of the slip, which involves fast real-time processing.Ministerio de Ciencia y Tecnología TIC2003 - 09817-C0

A content-based retrieval system for UAV-like video and associated metadata

In this paper we provide an overview of a content-based retrieval (CBR) system that has been specifically designed for handling UAV video and associated meta-data. Our emphasis in designing this system is on managing large quantities of such information and providing intuitive and efficient access mechanisms to this content, rather than on analysis of the video content. The retrieval unit in our system is termed a "trip". At capture time, each trip consists of an MPEG-1 video stream and a set of time stamped GPS locations. An analysis process automatically selects and associates GPS locations with the video timeline. The indexed trip is then stored in a shared trip repository. The repository forms the backend of a MPEG-211 compliant Web 2.0 application for subsequent querying, browsing, annotation and video playback. The system interface allows users to search/browse across the entire archive of trips and, depending on their access rights, to annotate other users' trips with additional information. Interaction with the CBR system is via a novel interactive map-based interface. This interface supports content access by time, date, region of interest on the map, previously annotated specific locations of interest and combinations of these. To develop such a system and investigate its practical usefulness in real world scenarios, clearly a significant amount of appropriate data is required. In the absence of a large volume of UAV data with which to work, we have simulated UAV-like data using GPS tagged video content captured from moving vehicles

Macromodelling for analog design and robustness boosting in bio-inspired computing models

Setting specifications for the electronic implementation of biological neural-network-like vision systems on-chip is not straightforward, neither it is to simulate the resulting circuit. The structure of these systems leads to a netlist of more than 100.000 nodes for a small array of 100×150 pixels. Moreover, introducing an optical input in the low level simulation is nowadays not feasible with standard electrical simulation environments. Given that, to accomplish the task of integrating those systems in silicon to build compact, low power consuming, and reliable systems, a previous step in the standard analog electronic design flux should be introduced. Here a methodology to make the translation from the biological model to circuit-level specifications for electronic design is proposed. The purpose is to include non ideal effects as mismatching, noise, leakages, supply degradation, feedthrough, and temperature of operation in a high level description of the implementation, in order to accomplish behavioural simulations that require less computational effort and resources. A particular case study is presented, the analog electronic implementation of the locust's Lobula Giant Movement Detector (LGMD), a neural structure that fires a collision alarm based on visual information. The final goal is a collision threat detection vision system on-chip for automotive applications.European Union IST-2001-38097, TIC2003 - 09817-C02-0