Key elements for machine vision are the intra-scene dynamic range of the optical front-end, and a data representation that is as independent as possible from the illumination level. Furthermore, combining an optical front-end and a processor on the same chip enables a single-chip vision system to perform image acquisition, analysis and decision-making. This paper presents a system-on-chip which combines a front-end pixel with a time-domain logarithmic encoding and a variable reference voltage, a 32b processor, a graphical processing unit, 128 KB or SRAM, and several communication interfaces.It offers a 132dB intra-scene dynamic range encoded logarithmically with 149 steps per decade while achieving an FPN of 0.51 LSB. Logarithmic encoding is exploited on-chip to efficiently compute the image contrast by simple subtractions between neighbouring pixels.

A 128 x 128 pixels, 120 dB vision sensor extracting at the pixel level the contrast magnitude and direction of local image features is used to implement a lane tracking system. The contrast representation (relative change of illumination) delivered by the sensor is independent of the illumination level. Together with the high dynamic range of the sensor, it ensures a very stable image feature representation even with high spatial and temporal inhomogeneities of the illumination. Dispatching off chip image feature is done according to the contrast magnitude, prioritizing features with high contrast magnitude. This allows to reduce drastically the amount of data transmitted out of the chip, hence the processing power required for sub-sequent processing stages. To compensate for the low fill factor (9%) of the sensor, micro-lenses have been deposited which increase the sensitivity by a factor of 5, corresponding to an equivalent of 2000 ASA. An algorithm exploiting the contrast representation output by the vision sensor has been developed to estimate the position of a vehicle relative to the road markings. The algorithm first detects the road markings based on the contrast direction map. Then, it performs quadratic fits on selected kernel of 3 by 3 pixels to achieve sub-pixel accuracy on the estimation of the lane marking positions. The resulting precision on the estimation of the vehicle lateral position is I cm. The algorithm performs efficiently under a wide variety of environmental conditions, including night and rainy conditions.

This vision sensor outputs luminance, contrast magnitude and contrast orientation of image features for surveillance and automotive applications. The sensor produces a contrast representation with a dynamic range of 120 dB and a sensitivity of 2%. The chip is fabricated in a 0.5 /spl mu/m 3M 2P process and dissipates 300 mW at 3.3 V.

This paper describes a sensor interface for metal-oxide chemical gas sensor for pollution detection. The function of the ASIC is to control the sensor working temperature by applying a programmable voltage with 10 bit resolution, to measure the resistance of the sensitive elements ranging from 5 k/spl Omega/ to 100 M/spl Omega/, measure the ambient temperature with an external NTC thermistor and offer a fully digital user interface. It gives the possibility to make low power and low cost high performance gas sensing microsystems for consumer application.

This application-specific integrated circuit (ASIC) computes two optically encoded positions, each engraved in a pattern onto one of a two-cylinder assembly. The cylinders are coupled by a torsion bar of known stiffness so that the difference between the two extracted positions provides a torque measurement to be used in next-generation automobile electrical power assisted steering (EPAS) systems. The cylinder positions are defined by 11b absolute-position encoders plus 7 additional bits of interpolated (relative) position between adjacent codes. The circuit is controlled and accessed via a serial peripheral interface (SPI).

The optical character-recognition (OCR) system described consists of a CMOS retina, an analog classifier IC and a microcontroller. The retina converts the parallel optical input into an oriented edge representation which is processed further and recognized by the classifier in real-time. The microcontroller postprocesses the time sequence of classifier outputs and provides timing and control. The system can be used as a handheld OCR scanner which processes the field of view 1000 times per second. The system output is the character string being scanned.