High sensitive NO2 gas sensor with low power consumption using selectively grown ZnO nanorods.

The noble gas sensor using multiple ZnO nanorods was fabricated with CMOS compatible process and sol-gel growth method on selective area and gas response characteristics to NO2 gas of the sensor device were investigated. We confirmed the sensors had high sensitive response denoted by the sensitivity of several tens for NO2 gas sensing and also showed pretty low power consumption close to 20 mW even though the recovery of resistance come up to almost the initial value.

A closely integrated digital image capture device for embedded applications

A modular image capture system with close integration to CCD cameras has been developed. The aim is to produce a system capable of integrating CCD sensor, image capture and image processing into a single compact unit. This close integration provides a direct mapping between CCD pixels and digital image pixels. The system has been interfaced to a digital signal processor board for the development and control of image processing tasks. These have included characterization and enhancement of noisy images from an intensified camera and measurement to subpixel resolutions. A highly compact form of the image capture system is in an advanced stage of development. This consists of a single FPGA device and a single VRAM providing a two chip image capturing system capable of being integrated into a CCD camera. A miniature compact PC has been developed using a novel modular interconnection technique, providing a processing unit in a three dimensional format highly suited to integration into a CCD camera unit. Work is under way to interface the compact capture system to the PC using this interconnection technique, combining CCD sensor, image capture and image processing into a single compact unit. ©2005 Copyright SPIE - The International Society for Optical Engineering.

SOI diode temperature sensor operated at ultra high temperatures-a critical analysis

This paper investigates the performance of diode temperature sensors when operated at ultra high temperatures (above 250°C). A low leakage Silicon On Insulator (SOI) diode was designed and fabricated in a 1 μm CMOS process and suspended within a dielectric membrane for efficient thermal insulation. The diode can be used for accurate temperature monitoring in a variety of sensors such as microcalorimeters, IR detectors, or thermal flow sensors. A CMOS compatible micro-heater was integrated with the diode for local heating. It was found that the diode forward voltage exhibited a linear dependence on temperature as long as the reverse saturation current remained below the forward driving current. We have proven experimentally that the maximum temperature can be as high as 550°C. Long term continuous operation at high temperatures (400°C) showed good stability of the voltage drop. Furthermore, we carried out a detailed theoretical analysis to determine the maximum operating temperature and exlain the presence of nonlinearity factors at ultra high temperatures. © 2008 IEEE.

Improved infrared thermal imaging of a CMOS MEMS device

We report a technique which can be used to improve the accuracy of infrared (IR) surface temperature measurements made on MEMS (Micro-Electro-Mechanical- Systems) devices. The technique was used to thermally characterize a SOI (Silicon-On-Insulator) CMOS (Complementary Metal Oxide Semiconductor) MEMS thermal flow sensor. Conventional IR temperature measurements made on the sensor were shown to give significant surface temperature errors, due to the optical transparency of the SiO 2 membrane layers and low emissivity/high reflectivity of the metal. By making IR measurements on radiative carbon micro-particles placed in isothermal contact with the device, the accuracy of the surface temperature measurement was significantly improved. © 2010 EDA Publishing/THERMINIC.

Thermal characterization of SOI CMOS micro hot-plate gas sensors

This work reports on thermal characterization of SOI (silicon on insulator) CMOS (complementary metal oxide semiconductor) MEMS (micro electro mechanical system) gas sensors using a thermoreflectance (TR) thermography system. The sensors were fabricated in a CMOS foundry and the micro hot-plate structures were created by back-etching the CMOS processed wafers in a MEMS foundry using DRIE (deep reactive ion etch) process. The calibration and experimental details of the thermoreflectance based thermal imaging setup, used for these micro hot-plate gas sensor structures, are presented. Experimentally determined temperature of a micro hot-plate sensor, using TR thermography and built-in silicon resistive temperature sensor, is compared with that estimated using numerical simulations. The results confirm that TR based thermal imaging technique can be used to determine surface temperature of CMOS MEMS devices with a high accuracy. © 2010 EDA Publishing/THERMINIC.

A novel ultra low power temperature sensor for UHF RFID tag chip

A novel ultra low power temperature sensor for UHF RFID tag chip is presented. The sensor consists of a constant pulse generator, a temperature related oscillator, a counter and a bias. Conversion of temperature to digital output is fulfilled by counting the number of the clocks of the temperature related oscillator in a constant pulse period. The sensor uses time domain comparing, where high power consumption bandgap voltage references and traditional ADCs are not needed. The sensor is realized in a standard 0.18 mu m CMOS process, and the area is only 0.2mm(2). The accuracy of the temperature sensor is +/- 1 degrees C after calibration. The power consumption of the sensor is only 0.9 mu W.

A Novel CMOS Color Pixel for Vision Chips

This paper presents a novel CMOS color pixel with a 2D metal-grating structure for real-time vision chips. It consists of an N-well/P-substrate diode without salicide and 2D metal-grating layers on the diode. The periods of the 2D metal structure are controlled to realize color filtering. We implemented sixteen kinds of the pixels with the different metal-grating structures in a standard 0.18 mu m CMOS process. The measured results demonstrate that the N-well/P-substrate diode without salicide and with the 2D metal-grating structures can serve as the high speed RGB color active pixel sensor for real-time vision chips well.

Assessing the potential of VEGETATION sensor data for mapping snow and ice cover: a Normalized Difference Snow and Ice Index

The VEGETATION (VGT) sensor in SPOT 4 has four spectral bands that are equivalent to Landsat Thematic Mapper (TM) bands (blue, red, near-infrared and mid-infrared spectral bands) and provides daily images of the global land surface at a 1-km spatial resolution. We propose a new index for identifying and mapping of snow ice cover, namely the Normalized Difference Snow/Ice Index (NDSII), which uses reflectance values of red and mid-infrared spectral bands of Landsat TM and VGT. For Landsat TM data, NDSII is calculated as NDSIITM =(TM3 -TM5)/(TM3 +TM5); for VGT data, NDSII is calculated as NDSIIVGT =(B2- MIR)/(B2 + MIR). As a case study we used a Landsat TM image that covers the eastern part of the Qilian mountain range in the Qinghai-Xizang (Tibetan) plateau of China. NDSIITM gave similar estimates of the area and spatial distribution of snow/ice cover to the Normalized Difference Snow Index (NDSI=(TM2-TM5)/(TM2+TM5)) which has been proposed by Hall et al. The results indicated that the VGT sensor might have the potential for operational monitoring and mapping of snow/ice cover from regional to global scales, when using NDSIIVGT.

Cellular automata and non-static image processing for embodied robot systems on a massively parallel processor array

Huelse, M, Barr, D R W, Dudek, P: Cellular Automata and non-static image processing for embodied robot systems on a massively parallel processor array. In: Adamatzky, A et al. (eds) AUTOMATA 2008, Theory and Applications of Cellular Automata. Luniver Press, 2008, pp. 504-510. Sponsorship: EPSRC

Deformable Prototypes for Encoding Shape Categories in Image Databases

We describe a method for shape-based image database search that uses deformable prototypes to represent categories. Rather than directly comparing a candidate shape with all shape entries in the database, shapes are compared in terms of the types of nonrigid deformations (differences) that relate them to a small subset of representative prototypes. To solve the shape correspondence and alignment problem, we employ the technique of modal matching, an information-preserving shape decomposition for matching, describing, and comparing shapes despite sensor variations and nonrigid deformations. In modal matching, shape is decomposed into an ordered basis of orthogonal principal components. We demonstrate the utility of this approach for shape comparison in 2-D image databases.

Self-Organizing Hierarchical Knowledge Discovery by an ARTMAP Image Fusion System

Classifying novel terrain or objects front sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods described here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among objects are assumed to be unknown to the automated system or the human user. The ARTMAP information fusion system used distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierarchical knowledge structures. The system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships.

Estimating Sensor Motion from Wide-Field Optical Flow on a Log-Dipolar Sensor

Log-polar image architectures, motivated by the structure of the human visual field, have long been investigated in computer vision for use in estimating motion parameters from an optical flow vector field. Practical problems with this approach have been: (i) dependence on assumed alignment of the visual and motion axes; (ii) sensitivity to occlusion form moving and stationary objects in the central visual field, where much of the numerical sensitivity is concentrated; and (iii) inaccuracy of the log-polar architecture (which is an approximation to the central 20°) for wide-field biological vision. In the present paper, we show that an algorithm based on generalization of the log-polar architecture; termed the log-dipolar sensor, provides a large improvement in performance relative to the usual log-polar sampling. Specifically, our algorithm: (i) is tolerant of large misalignmnet of the optical and motion axes; (ii) is insensitive to significant occlusion by objects of unknown motion; and (iii) represents a more correct analogy to the wide-field structure of human vision. Using the Helmholtz-Hodge decomposition to estimate the optical flow vector field on a log-dipolar sensor, we demonstrate these advantages, using synthetic optical flow maps as well as natural image sequences.

Miniaturised multi-MEMS sensor development

Complex systems, from environmental behaviour to electronics reliability, can now be monitored with Wireless Sensor Networks (WSN), where multiple environmental sensors are deployed in remote locations. This ensures aggregation and reading of data, at lower cost and lower power consumption. Because miniaturisation of the sensing system is hampered by the fact that discrete sensors and electronics consume board area, the development of MEMS sensors offers a promising solution. At Tyndall, the fabrication flow of multiple sensors has been made compatible with CMOS circuitry to further reduce size and cost. An ideal platform on which to host these MEMS environmental sensors is the Tyndall modular wireless mote. This paper describes the development and test of the latest sensors incorporating temperature, humidity, corrosion, and gas. It demonstrates their deployment on the Tyndall platform, allowing real-time readings, data aggregation and cross-correlation capabilities. It also presents the design of the next generation sensing platform using the novel 10mm wireless cube developed by Tyndall.

Image processing chip for small object detection

A new, front-end image processing chip is presented for real-time small object detection. It has been implemented using a 0.6 µ, 3.3 V CMOS technology and operates on 10-bit input data at 54 megasamples per second. It occupies an area of 12.9 mm×13.6 mm (including pads), dissipates 1.5 W, has 92 I/O pins and is to be housed in a 160-pin ceramic quarter flat-pack. It performs both one- and two-dimensional FIR filtering and a multilayer perceptron (MLP) neural network function using a reconfigurable array of 21 multiplication-accumulation cells which corresponds to a window size of 7×3. The chip can cope with images of 2047 pixels per line and can be cascaded to cope with larger window sizes. The chip performs two billion fixed point multiplications and additions per second.

Programmable image processing chip

A new high performance, programmable image processing chip targeted at video and HDTV applications is described. This was initially developed for image small object recognition but has much broader functional application including 1D and 2D FIR filtering as well as neural network computation. The core of the circuit is made up of an array of twenty one multiplication-accumulation cells based on systolic architecture. Devices can be cascaded to increase the order of the filter both vertically and horizontally. The chip has been fabricated in a 0.6 µ, low power CMOS technology and operates on 10 bit input data at over 54 Megasamples per second. The introduction gives some background to the chip design and highlights that there are few other comparable devices. Section 2 gives a brief introduction to small object detection. The chip architecture and the chip design will be described in detail in the later sections.