Camera-on-Chip: Low Power Sensors for Visual Information Extraction

Monday, March 24, 2008
7:00 PM
Free and open to the public

Traditional approaches to visual information processing have relayed on CCD/CMOS cameras, analog-to-digital conversion and power-hungry digital signal processors. These approaches are very complex, consume lot of power and often prevent real time extraction of relevant visual information. In order to alleviate some of these problems for high image data rate processing, I will discuss several computational image sensors capable of extracting visual information at the sensor level. I will approach the subject of integrated computational sensors from the information flow perspective. First, I will introduce a novel current mode pixel, which operates with reduced number of transistors per pixel. The new imaging pixel allows for high resolution and low noise current mode imaging. The fundamental noise limitation of this novel pixel will be presented and theoretical noise models will be discussed.

The second imaging sensor will present low power analog techniques for focal plane spatiotemporal image processing. This imaging sensor borrows essential ideas from biology and implements most of the computation in the analog domain. Most of the processing on the raw image is performed during read out, avoiding the power consumption problems and complexity of digital circuits and ADCs. Applications for this focal plane image sensor include motion detection and wave front phase correction.

The final imaging sensor will present a novel sensory system capable of extracting polarization information in real time. Polarization is one of the fundamental properties of light which has been ignored in traditional image sensors. Our research efforts uniquely combine advancements in polymer technology, nano-fabrication and CMOS imaging technology in order to create the first high resolution polarization image sensor. Applications for the polarization image sensor will be presented.

I will conclude with a discussion on image processing architecture implemented in a novel 3-D Silicon on Insulator (SOI) stack fabrication process.

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Viktor Gruev

Postdoctoral Researcher
University of Illinois at Urbana Champaign

Viktor Gruev is an associate professor in the department of Electrical and Computer Engineering at University of Illinois at Urbana Champaign. Prior to joining UIUC, he was an associate professor in the Department of Computer Science and Engineering at Washington University in St. Louis.  Prof. Gruev received his B.S. in Electrical Engineering from Southern Illinois University in Carbondale in 1998. He completed his M.S. and PhD. in electrical engineering from Johns Hopkins University in 2000 and 2004 respectively. He has received numerous awards for his research on imaging sensors and their application in the medical field, including the 2016 Donald H Fink award and the 2015 best paper and best demo at the IEEE Circuits and Systems Symposium. His current research focuses on developing bio-inspired sensory technology to address medical needs in resources limited hospitals.