VLSI implementation of an application-specific vision chip for overtake monitoring, real time eye tracking, and automated visual inspection

With regard to application-specific constraints such as size, power consumption, and price, many real time vision tasks are still too demanding for today's state-of-the-art hardware. This is especially true for purely digital hardware systems. As an interesting alternative, we investigated the implementation of smart vision algorithms by an application-specific vision chip featuring combined analog and digital processing. The analog part implements computationally intensive operations in a massively parallel array, which allows to realize the remaining operations by a reduced complexity dedicated digital processor. This paper reports on the systematic design and VLSI implementation of dedicated vision chips for automotive image processing, eye tracking, and visual inspection.

[1]  Hans-Hellmut Nagel,et al.  On the Estimation of Optical Flow: Relations between Different Approaches and Some New Results , 1987, Artif. Intell..

[2]  J. L. White,et al.  An active resistor network for Gaussian filtering of images , 1991 .

[3]  Woodrow Barfield,et al.  Virtual environments and advanced interface design , 1995 .

[4]  Charles Sodini,et al.  Switched capacitor networks for focal plane image processing systems , 1992, IEEE Trans. Circuits Syst. Video Technol..

[5]  Andreas König,et al.  A transparent and flexible development environment for rapid design of cognitive systems , 1998, Proceedings. 24th EUROMICRO Conference (Cat. No.98EX204).

[6]  S. Getzlaff,et al.  Systematic design of an embedded neural system for automated visual consumption acquisition , 1999, Proceedings of the Seventh International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems.

[7]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[8]  Stephen M. Smith,et al.  ASSET-2: real-time motion segmentation and shape tracking , 1995, Proceedings of IEEE International Conference on Computer Vision.

[9]  Heinrich Klar,et al.  A New Bio-inspired Algorithm for Early Vision Edge Detection and Image Segmentation , 1997, IWANN.