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CMOS image sensors for sensor networks

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Abstract

We report on two generations of CMOS image sensors with digital output fabricated in a 0.6 μm CMOS process. The imagers embed an ALOHA MAC interface for unfettered self-timed pixel read-out targeted to energy-aware sensor network applications. Collision on the output is monitored using contention detector circuits. The image sensors present very high dynamic range and ultra-low power operation. This characteristics allow the sensor to operate in different lighting conditions and for years on the sensor network node power budget.

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References

  1. Y. Liu, W. Gao, H. Yao, S. Liu, and L. Wang, “Fast moving region detection scheme in ad hoc sensor network.” In Proceedings Lecture Notes In Computer Science, vol. 3212, pp. 520–527, 2004.

  2. E.M.C.F. Chiasserini, “Energy-efficient coding and error control for wireless video-surveillance networks.” Telecommunication Systems, vol. 26, pp. 369–387, 2004.

  3. M. Tehrani, P. Bangchang, T. Fujii, and M. Tanimoto, “The optimization of distributed processing for arbitrary view generation in camera sensor networks.” IEICE Transactions On Fundamentals Of Electronics Communications And Computer Sciences, vol. 8, pp. 1863–1870, 2004.

  4. W. Yang, “A wide-dynamic range, low-power photosensor array,” In IEEE International Solid-State Circuits Conference, ISSCC, San Francisco, CA, 1994, pp. 230–231.

  5. K. Cho, “A 1.2 V micropower CMOS active pixel image sensor for portable applications.” In IEEE International Solid-State Circuits Conference, ISSCC, San Francisco, CA, 2000, pp. 114–115.

  6. K. Cho, A. Krymski, and E. Fossum, “A 1.5-V 550-μW 176×144 autonomous CMOS active pixel image sensor.” IEEE Transactions on Electron Devices, vol. 50, no. 1, pp. 96–105, 2003.

  7. Various authors, In Proceedings of IEEE Special Issue on Sensor Networks. IEEE, Aug. 2003.

  8. P. Julian, A. Andreou, L. Riddle, S. Shamma, and G. Cauwenberghs, “A comparative study of sound localization algorithms for energy aware sensor network nodes.” IEEE Transactions On Circuits And Systems I: Regular Papers, vol. 51, pp. 640–648, April 2004.

  9. K.A. Boahen, “Point-to-point connectivity between neuromorphic chips using address events.” IEEE Trans. Circuits and Systems-II: Analog and Digital Signal Processing, vol. 47, no. 5, pp. 416–434, 2000.

  10. E. Culurciello, R. Etienne-Cummings, and K.A. Boahen, “A biomorphic digital image sensor.” IEEE Journal of Solid-State Circuits, vol. 38, no. 2, pp. 281–294, 2003.

  11. E. Culurciello and R. Etienne-Cummings, “Second generation of high dynamic range, arbitrated digital imager.” In IEEE International Symposium on Circuits and Systems, ISCAS, vol. 4, Vancouver, Canada, 2004, pp. IV–828–31.

  12. N. Abramson, “THE ALOHA SYSTEM—a nother alternative for computer communications.” In Proc. 1970 Fall Joint Computer Conference, 1970, pp. 281–285.

  13. B. Leibowitz, B. Boser, and K. Pister, “CMOS ”smart pixel” for free-space optical communication.” In Proceedings SPIE, vol. 4306, SPIE, 2001, pp. 308–318.

  14. B. Warneke, M. Last, B. Liebowitz, and K. Pister, “Smart dust: communicating with a cubic-millimeter computer.” Computer, vol. 34, pp. 44–51, 2001.

  15. SMal Camera Technologies, “IM-001 model series,” URL http://www.smalcamera.com/.

  16. Micron semiconductors. “Model MT9V012,” URL http://micron.com/products/imaging/.

  17. Agilent Camera Modules and Image Sensors, “Model ADCM-1650-3011” URL http://www.home.agilent.com/.

  18. C. Fermuller, Y. Aloimonos, P. Baker, R. Pless, J. Neumann, and B. Stuart, “Multi-camera networks: eyes from eyes.” In Proceedings of IEEE Workshop on Omnidirectional Vision, 2000, 2000, vol. 12, pp. 11–18.

  19. P. Doubek, I. Geys, T. Svoboda, and L.V. Gool, Cinematographic Rules Applied to a Camera Network. Omnivis, 2004.

  20. L. McIlrath, “A low-power low-noise ultrawide-dynamic-range CMOS imager with pixel-parallel A/D conversion.” IEEE Journal of Solid-State Circuits, vol. 36, no. 5, pp. 846–853, 2001.

  21. M. Rahimi, D. Estrin, R. Baer, H. Uyeno, and J. Warrior, “Cyclops: image sensing and interpretation in wireless networks.” In Second ACM Conference on Embedded Networked Sensor Systems, SenSys, Baltimore, MD, 2004.

  22. T. Ko and N. Berry, “Distributed feature extraction for event identification.” In Ambient Intelligence: Second European Symposium, EUSAIP roceedings, vol. 3295. Eindhoven, The Netherlands, 2004, pp. 136–147.

  23. PASTA, PASTA Microsensor 1.0 Developers Manual, USC ISI, 2005, http://pasta.east.isi.edu/

  24. D. Hymer, “Soil water evaluation using a hydrologic model and calibrated sensor network.” Soil Science Society of America Journal, vol. 64, pp. 319–327, 2000.

  25. M. Goodchild, “Geographic information science and systems for environmental management.” Annual Review of Energy and the Environment, vol. 28, p. 493, 2003.

  26. K. Yun et al., “A miniaturized low-power wireless remote environmental monitoring system based on electrochemical analysis.” Sensors and Actuators B: Chemical, vol. 102, pp. 27–35, 2004.

  27. R. Szewczyk, E. Osterweil, J. Polastre, M. Hamilton, A. Mainwaring, and D. Destrin, “Habitat monitoring with sensor networks.” Communications of the ACM, vol. 47, pp. 34–41, 2004.

  28. J. Kumagai, “The secret life of birds.” IEEE Spectrum, vol. 41, pp. 42–50, 2004.

  29. R.J. Nemzek and J. Dreicer, “Distributed sensor networks for detection of mobile radioactive sources.” IEEE Transactions on Nuclear Science, vol. 51, pp. 1693–1701, 2004.

  30. R. Brooks, D. Friedlander, J. Koch, and S. Phoha, “Tracking multiple targets with self-organizing distributed ground sensors.” Journal of Parallel and Distributed Computing, vol. 64, pp. 874–885, 2004.

  31. K. Morioka, J. Lee, and H. Hashimoto, “Human-following mobile robot in a distributed intelligent sensor network.” IEEE Transactions on Industrial Electronics, vol. 51, pp. 229–238, 2004.

  32. M. Duarte and H. Yu, “Vehicle classification in distributed sensor networks.” Journal of Parallel and Distributed Computing, vol. 64, pp. 826–839, 2004.

  33. E. Culurciello and A.G. Andreou, “ALOHA CMOS imager.” In IEEE International Symposium on Circuits and Systems, ISCAS, Vancouver, Canada, 2004, pp. IV–956–9.

  34. C. Mead and M. Mahowald, A Silicon Model of Early Visual Processing. Pergamon Press, 1988.

  35. M. Sivilotti, “Wiring considerations in analog VLSI systems with applications to field programmable networks.” Ph.D. dissertation, California Institute of Technology, 1991.

  36. A. Andreou and K. Boahen, “A 590,000 transistor, 48,000 pixel contrast sensitive, edge enhancing CMOS imager-silicon retina.” In Preceedings of the 16th Conference on Advaced Research in VLSI, Chapel Hill, NC, 1995, pp. 225–240.

  37. Z. Kalayjian and A. Andreou, “Asynchronous communication of 2d motion information using winnertake-all arbitration,” Journal of Analog Integrated Circuits and Signal Processing, vol. 103–109, p. 13, 1997.

  38. K. Boahen, Communicating Neuronal Ensembles Between Neuromorphic Chips, Neuromorphic Systems Engineering. Kluwer Academic Publishers, ch. 11, pp. 229–261, 1998.

  39. N. Stevanovic, “A CMOS image sensor for high-speed imaging.” In IEEE International Solid-State Circuits Conference, ISSCC, San Francisco, CA, 2000, pp. 104–105.

  40. O. Yadid-Pecht and A. Belenky, “In-pixel autoexposure CMOS APS.” IEEE Journal of Solid-State Circuits, vol. 38, pp. 1425–1428, 2003.

  41. E. Culurciello and A. Andreou, “A comparative study of access topologies for chip-level address-event communication channels.” IEEE Transactions On Neural Networks, vol. 14, pp. 1266–1277, 2003 (special Issue On Hardware Implementations).

  42. K. Boahen, “Retinomorphic vision systems.” IEEE MicroNeuro, pp. 2–14, 1996.

  43. E. Fossum, “CMOS image sensors: Electronic camera-on-a-chip.” IEEE Transactions on Electron Devices, vol. 44, no. 10, pp. 1689–1698, 1997.

  44. S. Kleinfelder, S. Lim, X. Liu, and A.E. Gamal, “A 10000 frames/s CMOS digital pixel sensor.” IEEE Journal of Solid-State Circuits, vol. 36, no. 12, pp. 2049–2059, 2001.

  45. A. Mortara and E. Vittoz, “A communication architecture tailored for analog VLSI artificial neural networks: Intrinsic performance and limitations.” IEEE Transactions on Neural Networks, vol. 5, no. 3, pp. 459–466, 1994.

  46. A. Mortara, E. Vittoz, and P. Venier, “A communication scheme for analog VLSI perceptive systems.” IEEE Journal of Solid-State Circuits, vol. 30, no. 6, pp. 660–669, 1995.

  47. M.M.A. Abusland and T. Lande, “A VLSI communication architecture for stochastically pulse-encoded analog signals.” IEEE International Symposium of Circuits and Systems, ISCAS, Atlanta, Georgia, vol. 3, pp. 401–404, 1996.

  48. O. Yadid-Pecht and E. Fossum, “Wide intrascene dynamic range CMOS APS using dual sampling.” IEEE Transactions on Electron Devices, vol. 44, no. 10, pp. 1721–1723, 1997.

  49. D. Yang, A.E. Gamal, B. Fowler, and H. Tian, “A 640×512 CMOS image sensor with ultrawide dynamic range floating-point pixel-level ADC.” IEEE Journal of Solid-State Circuits, vol. 34, pp. 1821–1833, 1999.

  50. O. Schrey, R. Hauschild, B. Hosticka, U. Lurgel, and M. Schwarz, “A locally adaptive CMOS image sensor with 90 dB dynamic range.” In IEEE International Solid-State Circuits Conference, ISSCC, 1999, pp. 310–311.

  51. M. Schanz, C. Nitta, A. Bubmann, B. Hosticka, and R. Wertheimer, “A high-dynamic-range CMOS image sensor for automotive applications.” IEEE Journal of Solid-State Circuits, vol. 35, pp. 932–938, 2000.

  52. D. Hubel, Eye, Brain, and Vision. Scientific American Library (HPHLP), 1988.

  53. B. Wandell, Foundations of Vision. Sinauer Associates Inc. Publishers, 1995.

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Correspondence to Eugenio Culurciello.

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Eugenio Culurciello (S’97–M’99) received the Ph.D. degree in Electrical and Computer Engineering in 2004 from Johns Hopkins University, Baltimore, MD. In July 2004 he joined the department of Electrical Engineering at Yale University, where he is currently an assistant professor. He founded and instrumented the E-Lab laboratory in 2004. His research interest is in analog and mixed-mode integrated circuits for biomedical applications, sensors and networks, biological sensors, Silicon on Insulator design and bio-inspired systems.

Andreas G. Andreou received his Ph.D. in electrical engineering and computer science in 1986 from Johns Hopkins University. Between 1986 and 1989 he held post-doctoral fellow and associate research scientist positions in the Electrical and Computer engineering department while also a member of the professional staff at the Johns Hopkins Applied Physics Laboratory. Andreou became an assistant professor of Electrical and Computer engineering in 1989, associate professor in 1993 and professor in 1996. He is also a professor of Computer Science and of the Whitaker Biomedical Engineering Institute and director of the Institute’s Fabrication and Lithography Facility in Clark Hall. He is the co-founder of the Johns Hopkins University Center for Language and Speech Processing. Between 2001 and 2003 he was the founding director of the ABET accredited undergraduate Computer Engineering program. In 1996 and 1997 he was a visiting professor of the computation and neural systems program at the California Institute of Technology. In 1989 and 1991 he was awarded the R.W. Hart Prize for his work on mixed analog/digital integrated circuits for space applications. He is the recipient of the 1995 and 1997 Myril B. Reed Best Paper Award and the 2000 IEEE Circuits and Systems Society, Darlington Best Paper Award. During the summer of 2001 he was a visiting professor in the department of systems engineering and machine intelligence at Tohoku University. In 2006, Prof. Andreou was elected as an IEEE Fellow and a distinguished lecturer of the IEEE EDS society.

Andreou’s research interests include sensors, micropower electronics, heterogeneous microsystems, and information processing in biological systems. He is a co-editor of the IEEE Press book: Low-Voltage/Low-Power Integrated Circuits and Systems, 1998 (translated in Japanese) and the Kluwer Academic Publishers book: Adaptive Resonance Theory Microchips, 1998. He is an associate editor of IEEE Transactions on Circuits and Systems I.

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Culurciello, E., Andreou, A.G. CMOS image sensors for sensor networks. Analog Integr Circ Sig Process 49, 39–51 (2006). https://doi.org/10.1007/s10470-006-8737-x

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