A Design of Digital Image Sensor Based on UWB

  IJCOT-book-cover
 
International Journal of Computer & Organization Trends (IJCOT)          
 
© 2014 by IJCOT Journal
Volume - 4 Issue - 1 
Year of Publication : 2014
Authors : Dr. G.Natarajan , B.Karthiga , N.Kannan
  10.14445/22492593/IJCOT-V5P305

MLA

Dr. G.Natarajan , B.Karthiga , N.Kannan . "A Design of Digital Image Sensor Based on UWB", International Journal of Computer & organization Trends (IJCOT) , V4(1):34-37 Jan - Feb 2014, ISSN:2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.

Abstract—A low power temporal-difference image sensor with wireless communication capability designed specifically for imaging sensor networks. The event-based image sensor features a 64 X 64 pixel arrays that capture and compressed the motion based images and compute the temporal difference images, while continuously monitoring for photocurrent changes. An ultra-wide-band radio channel allows transmitting digital temporal difference images wirelessly to a receiver with high rates and reduced power consumption. The sensor can enable the UWB when it detects a specific number of pixels intensity modulations, so that only significant frames are communicated. By the help of encoding technique the error rate is reduced up to 10% compared to previous work.

References-

[1] K.Y.Min and J.W.Chon, “A real-timejpeg encoder for 1.3 megapixel CMOS image sensor SOC,” in Proc. IEEE 30thAnnu. Conf. Ind.Electron. Soc., 2004, pp. 2633–2636.
[2] Y.Nishikawa, S.Kawahito, M.Furuta, and T. Tamura, “A high-speedCMOS image sensor with on-chip parallel image compression circuits,” in Proc. IEEE Custom Integr.CircuitsConf., 2007, pp.833–836.
[3] A.Nilchi, J.Aziz, and R.Genov, “Focal-plane algorithmically-multiplyingCMOS computational image sensor,” IEEE J. Solid-State Circuits,vol. 44, pp. 1829–1839, Sep. 2009.
[4] S.Chen, A. Bermak, and Y. Wang, “A CMOS image sensor withon-chip image compression based on predictive boundary adaptation and memory less QTD algorithm,” IEEE Trans. Very Large ScaleIntegr. (VLSI) Syst., vol. 19, no. 4, pp. 538–547, Apr. 2011.
[5]P.Lichtsteiner, C.Posch & T. Delbruck, “A 128x128 120db 15µs latency asynchronous temporal contrast vision sensor,” IEEE J. Solid-State Circuits, vol. 43, no. 2, pp. 566–576, Feb. 2008.
[6] M. Gottardi, N. Massari& S. A. Jawed, “A 100µW 128x64pixels contrast-based asynchronous binary vision sensor for sensor networks applications,” IEEE J. Solid-State Circuits, vol. 43, no. 5, pp.1582–1592, May 2009.
[7]E. Culurciello, R. Etienne-Cummings, and K. Boahen, “Arbitrated address event representation digital image sensor,” in Proc. IEEE Int.Solid-State Circuits Conf., 2001, pp. 92–93
[8] S. B. T. Wang, A. M. Niknejad, and R. W. Brodersen, “Design of a sub-MW 960-MHz UWB CMOS LNA,” IEEE J. Solid-State Circuits,vol. 41, no. 11, pp. 2449–2456, Nov. 2006
[9] T.-A. Phan and S.-G. Lee, “Low-power CMOS energy detection transceiver for UWB impulse radio system,” in Proc. IEEE CustomIntegr. Circuits Conf., 2007, pp. 675–678
[10] V. Gruev and R. Etienne-Cummings, “A pipelined temporal difference imager,” IEEE J. Solid-State Circuits, vol. 39, no. 3, pp. 538–543, Mar.2004.
[11] U.Mallik,M. Clapp, E. Choi, G. Cauwenberghs, and R. Etienne-Cummings, “Temporal change threshold detection imager,” in Proc. IEEEInt. Solid-State Circuits Conf., 2005, pp. 362–603.
[12] A. Chandrakasan, F. Lee, D. Wentzloff, V. Sze, B. Ginsburg, P.Mercier, D. Daly, and R. Blazquez, “Low-power impulse UWB architectures and circuits,” Proc. IEEE, vol. 97, no. 2, pp. 332–352,Feb. 2009.
[13] A. Dickinson, B. Ackland, E.-S. Eid, D. Inglis, and E. Fossum, “A 256x256 CMOS active pixel image sensor with motion detection,” inProc. IEEE Int. Solid-State Circuits Conf., 1995, pp. 226–227.
[14] W. Tang and E. Culurciello, “A low-power high-speed ultra-wide band pulse radio transmission systemSyst., 2008, pp. 1064–1067.,” IEEE Trans. Biomed. Circuits Syst., pp. 286–292, 2009.
[15] Jaein Jeong and Cheng Tien Ee, “Forward error correction in sensor networks, in University of California., Berkeley” May 16-2003.

Keywords—Image sensor, motion detection, temporal-difference, Ultra-Wide-Band (UWB), wireless sensor network.