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Quantum–Dot Cellular Automata Design for Median Filtering and Mathematical Morphology Operations on Binary Images

  • Fotios K. Panagiotopoulos
  • Vassilios A. Mardiris
  • Vassilios Chatzis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7495)

Abstract

The continuing development of smaller electronic devices into the nanometer regime offers great possibilities of highly parallel computing systems, as it allows to reduce power consumption and device sizes and to increase operating speed. Quantum-dot Cellular Automata (QCA) has been proposed as an alternative for nanoelectronic devices and introduces a new opportunity for the design of highly parallel algorithms and architectures. Its benefits are the fast speed, very small size, high density and low energy consumption. These advantages can be very useful for various real time image processing applications. Complex image processing algorithms include in many cases the well-known binary median filter and mathematical morphology operations such as dilation and erosion. In this paper we propose and simulate two innovative QCA circuits which implement the dilation and the erosion.

Keywords

Dot Cellular Automata circuit design circuit simulation nanoelectronics median filter mathematical morphology binary image 
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References

  1. 1.
    Huang, T.S. (ed.): Two-dimensional Digital Signal Processing II: Transforms and Median Filters. Springer, New York (1981)Google Scholar
  2. 2.
    Gallagher, N.C., Wise, G.L.: A Theoretical Analysis of the Properties of Median Filters. IEEE Transactions on Acoustic, Speech and Signal Processing, ASSP 29, 1136–1141 (1981)CrossRefGoogle Scholar
  3. 3.
    Breveglieri, L., Piuri, V.: Digital Median Filters. Journal of VLSI Signal Processing 31, 191–206 (2002)zbMATHCrossRefGoogle Scholar
  4. 4.
    Serra, J., Soille, P.: Mathematical Morphology and its Applications to Image Processing. Kluwer, Norwell (1994)zbMATHCrossRefGoogle Scholar
  5. 5.
    Matheron, G.: Random Sets and Integral Geometry. Wiley, N.Y. (1975)zbMATHGoogle Scholar
  6. 6.
    Chatzis, V., Pitas, I.: A Generalized Fuzzy Mathematical Morphology and its Application in Robust 2D and 3D Object Representation. IEEE Trans. on Image Processing 9(10), 1798–1810 (2000)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Koskinen, L., Astola, J., Neuvo, Y.: Soft morphological filters. In: Proc. SPIE Symp. Image Algebra Morphological Image Processing, vol. 1568, pp. 262–270 (1991)Google Scholar
  8. 8.
    Bloch, I., Maitre, H.: Fuzzy mathematical morphologies: A comparative study. Pattern Recognit. 28, 1341–1387 (1995)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Maragos, P., Schafer, R.W.: Morphological Systems for Multidimensional Signal Processing. IEEE Proceedings 78(4), 690–710 (1990)CrossRefGoogle Scholar
  10. 10.
    Danielson, P.E., Levialdi, S.: Computer Architectures for Pictorial Information Systems. IEEE Computer Magazine, 53–67 (November 1981)Google Scholar
  11. 11.
    Reinhardt, J.M., Higgins, W.E.: Efficient morphological shape representation. IEEE Trans. Image Processing 5, 89–101 (1996)CrossRefGoogle Scholar
  12. 12.
    Venkateshwar Rao, D., Patil, S., Babu, N.A., Muthukumar, V.: Implementation and Evaluation of Image Processing Algorithms on Reconfigurable Architecture using C-based Hardware Descriptive Languages. International Journal of Theoretical and Applied Computer Sciences 1(1), 9–34 (2006)Google Scholar
  13. 13.
    Malamas, E.N., Malamos, A.G., Varvarigou, T.A.: Fast Implementation of Binary Morphological Operations on Hardware. Efficient Systolic Architectures Journal of VLSI Signal Processing 25, 79–93 (2000)Google Scholar
  14. 14.
    Nalpantidis, L., Amanatiadis, A., Sirakoulis, G.C., Gasteratos, A.: An Efficient Hierarchical Matching Algorithm for Processing Uncalibrated Stereo Vision Images and its Hardware Architecture. IET Image Processing 5(5), 481–492 (2011)CrossRefGoogle Scholar
  15. 15.
    Konstantinidis, K., Sirakoulis, G.C., Andreadis, I.: Design and Implementation of a Fuzzy Modified Ant Colony Hardware Structure for Image Retrieval. IEEE Transactions on Systems, Man and Cybernetics – Part C 50(3), 519–537 (2009)Google Scholar
  16. 16.
    The international technology roadmap for semiconductors: Emerging research devices 17 (2005), http://www.itrs.net/
  17. 17.
    Antonelli, D.A., Chen, D.Z., Dysart, T.J., Hu, X.S.: Quantum-dot Cellular Automata (QCA) circuit partitioning: Problem modeling and solutions. In: Proc. of Design Auto. Conf., San Diego, CA (June 2004)Google Scholar
  18. 18.
    Akeela, R., Wagh, M.D.: A Five-input Majority Gate in Quantum-dot Cellular Automata. NSTI-Nanotech, 2011 vol. 2 (2011), ISBN 978-1-4398-7139-3, http://www.nsti.org
  19. 19.
    Zhang, R., Walus, K., Wang, W., Jullien, G.A.: A majority reduction technique for adder structures in quantum-dot cellular. In: Proceedings of SPIE, vol. 5559, pp. 91–100 (2004)Google Scholar
  20. 20.
    Tougaw, P.D., Lent, C.S.: Logical devices implemented using quantum cellular automata. Journal of Applied Physics 75(3), 1818–1825 (1994), doi:10.1063/1.356375CrossRefGoogle Scholar
  21. 21.
    Wang, W., Walus, K., Jullien, G.A.: Quantum-Dot Cellular Automata Adders. In: IEEE International Conference on Nanotechnology IEEE-NANO, vol. 2, pp. 461–464 (2003), doi:10.1109/NANO.2003.1231818.Google Scholar
  22. 22.
    Fijany, A., Toomarian, N., Modarress, K., Spotnitz, M.: Bit-serial Adder Based on Quantum Dots. NASA technical report (January 2003)Google Scholar
  23. 23.
    Kim, K., Wu, K., Karri, R.: The Robust QCA Adder Designs Using Composable QCA Building Blocks. IEEE Transactions on CAD of Integrated Circuits and Systems 26(1), 176–183 (2007), doi:10.1109/TCAD.2006.883921CrossRefGoogle Scholar
  24. 24.
    Hänninen, I., Takala, J.: Arithmetic Design on Quantum-Dot Cellular Automata Nanotechnology. In: Bereković, M., Dimopoulos, N., Wong, S. (eds.) SAMOS 2008. LNCS, vol. 5114, pp. 43–52. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  25. 25.
    Mardiris, V.A., Karafyllidis, I.G.: Universal cellular automaton cell using quantum cellular automata. Electronics Letters 45(12), 607–609Google Scholar
  26. 26.
    Vankamamidi, V., Ottavi, M., Lombardi, F.: Two-Dimensional Schemes for Clock-ing/Timing of QCA Circuits. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 27(1), 34–44 (2008), doi:10.1109/TCAD.2007.907020CrossRefGoogle Scholar
  27. 27.
    Mardiris, V.A., Karafyllidis, I.G.: Design and simulation of modular quantum-dot cellular automata multiplexers for memory accessing. Journal of Circuits, Systems and Computers 19(2), 349–365Google Scholar
  28. 28.
    Mardiris, V.A., Karafyllidis, I.G.: Design and simulation of modular 2n to 1 quantum-dot cellular automata (QCA) multiplexers International. Journal of Circuit Theory and Applications 38(8), 771–785Google Scholar
  29. 29.
    Huang, J., Momenzadeh, M., Lombardi, F.: Analysis of missing and additional cell defects in sequential quantum-dot cellular automata. INTEGRATION, the VLSI Journal 40, 503–515 (2007), doi:10.1016/j.vlsi.2006.08.001CrossRefGoogle Scholar
  30. 30.
    Huang, J., Momenzadeh, M., Lombardi, F.: Design of sequential circuits by quantum-dot cellular automata. Microelectronics Journal 38, 525–537 (2007), doi:10.1016/j.mejo.2007.03.013CrossRefGoogle Scholar
  31. 31.
    Vankamamidi, V., Ottavi, M., Lombardi, F.: Tile-Based Design of a Serial Memory in QCA. In: Proceedings of the 15th ACM Great Lakes Symposium on VLSI, pp. 201–206 (2005), doi:10.1145/1057661.1057711Google Scholar
  32. 32.
    Vankamamidi, V., Ottavi, M., Lombardi, F.: A Serial Memory by Quantum-Dot Cellular Automata (QCA). IEEE Transactions on Computers 57(8), 606–618 (2008), doi:10.1109/TC.2007.70831MathSciNetCrossRefGoogle Scholar
  33. 33.
    Vankamamidi, V.M., Ottavi, M., Lombardi, F.: A Line-Based Parallel Memory for QCA Implementation. IEEE Transactions on Nanotechnology 4(6), 690–698 (2005), doi:10.1109/TNANO.2005.858589CrossRefGoogle Scholar
  34. 34.
    Niemier, M.T., Kontz, M.J., Kogge, P.: A Design of and Design Tools for a Novel Quantum Dot Based Microprocessor. In: Proceedings of the 37th Design Automation Conference, pp. 227–232 (2000), doi:10.1145/337292.337398Google Scholar
  35. 35.
    Crocker, M., Hu, X.S., Niemier, M., Yan, M., Bernstein, G.: PLAs in Quantum-Dot Cellular Automata. IEEE Transactions on Nanotechnology 7(3), 376–386 (2008), doi:10.1109/TNANO.2007.915022CrossRefGoogle Scholar
  36. 36.
    Helsingius, M., Kouosmanen, P., Astola, J.: Quantum-dot cells and their suability for nonlinear signal processing. In: Procceding og the IEEE EURASIP Workshop on Nonlinear Signal and Image Processing, NSIP 1999, vol. 2, pp. 659–663 (1999)Google Scholar
  37. 37.
    Cardenas-Barrera, J.L., Platoniotis, K.N., Venetsanopoulos, A.N.: QCA implementation of a multichannel filter for image processing. Math. Probl. Eng. 8(l), 87–99 (2002)zbMATHCrossRefGoogle Scholar
  38. 38.
    Amlani, I., Orlov, A.O., Toth, G., Bernstein, G.H., Lent, C.S., Snider, G.: Digital Logic Gate Using Quantum-dot Cellular Automata. Science 284(5412), 289–291 (1999), doi:10.1126/science.284.5412.289CrossRefGoogle Scholar
  39. 39.
    Lent, C.S., Tougaw, P.: A Device Architecture for Computing with Quantum Dots. Proceedings of the IEEE 85(4), 541–557 (1997), doi:10.1109/5.573740CrossRefGoogle Scholar
  40. 40.
    Navi, K., Sayedsalehi, S., Farazkish, R., Azghadi, M.R.: Five-input majority gate, a new device for quantum-dot cellular automata. Journal of Computational and Computational and Theoretical Nanoscience 7, 1546–1553 (2010)CrossRefGoogle Scholar
  41. 41.
    Navi, K., Farazkish, R., Sayedsalehi, S., Azghadi, M.R.: A new quantum-dot cellular automata full adder. Microelectronics Journal 7(22), 820–826 (2010)CrossRefGoogle Scholar
  42. 42.
    Azghadi, M.R., Kavehei, O., Navi, K.: A novel design for quantum-dot cellular automata cells and full-adders. Journal of Applied Sciences 7(22), 3460–3468 (2007)CrossRefGoogle Scholar
  43. 43.
    Amlani, I., Orlov, A.O., Kummamuru, R.K., Bernstein, G.H., Lent, C.S., Snider, G.L.: Experimental demonstration of a leadless quantum-dot cellular automata cell. Applied Physics Letters 77(5), 738–740 (2000), doi:10.1063/1.127103CrossRefGoogle Scholar
  44. 44.
    Walus, K., Dysart, T. J., Jullien, G. A., Budiman, A.R.: QCADesigner: A Rapid Design and Simulation Tool for Quantum-Dot Cellular Automata. IEEE Transactions on Nanotechnology 3(1), 26–31 (2004), doi:10.1109/TNANO.2003.820815CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Fotios K. Panagiotopoulos
    • 1
  • Vassilios A. Mardiris
    • 1
  • Vassilios Chatzis
    • 1
  1. 1.Department of Information ManagementTechnological Institute of KavalaGreece

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