MLP Neural Network Implementation on a SIMD Architecture

  • Salvatore Vitabile
  • Antonio Gentile
  • G. B. Dammone
  • Filippo Sorbello
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2486)


An Automatic Road Sign Recognition System A(RS) 2 is aimed at detection and recognition of one or more road signs from real-world color images. The authors have proposed an A(RS) 2 able to detect and extract sign regions from real world scenes on the basis of their color and shape features. Classification is then performed on extracted candidate regions using Multi-Layer Perceptron neural networks. Although system performances are good in terms of both sign detection and classification rates, the entire process requires a large computational time, so real-time applications are not allowed. In this paper we present the implementation of the neural layer on the Georgia Institute of Technology SIMD Pixel Processor. Experimental trials supporting the feasibility of real-time processing on this platform are also reported.


Automatic Road Sign Recognition System SIMD Pixel Processor 


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  1. 1.
    F. Sorbello, G. Gioiello, and S. Vitabile. Handwritten Character Recognition using a MLP, chapter 5, pages 91–119. L. C. Jain and B. Lazzerini-CRC Press, 1999.Google Scholar
  2. 2.
    S. Vitabile, G. Pilato, G. Pollaccia, F. Sorbello. Road Signs Recognition Using a Dynamic Pixel Aggregation Technique in the HSV Color Space. In Proc. of 11 ? International Conference on Image Analysis and Processing, Palermo-Italy, pp. 572–577, (2001), IEEE Computer Society Press.Google Scholar
  3. 3.
    S. Vitabile, A. Gentile, F. Sorbello. A Neural Network based Automatic Road Signs Recognizer. Proc. of 2002 IEEE World Congress on Computational Intelligence-International Joint Conference on Neural Networks (IJCNN), Honolulu-USA, pp. 2315–2320, IEEE Computer Society Press.Google Scholar
  4. 4.
    A. Gentile, J. Cruz-Rivera, D. Wills et al. Real-time image processing on a focal plane simd array, in parallel and distributed processing. Lecture Notes in Computer Science, (1586):400–405, 1999. Eds. J. Rolim et al.-Springer Verlag.CrossRefGoogle Scholar
  5. 5.
    A. Gentile, H.H. Cat, F. Kossentini, F. Sorbello, D.S. Wills. Real-Time Vector Quantization-based Image Compression on the SIMPil Low Memory SIMD Architecture. Proc. of the 1997 IEEE Intl. Performance, Computing, and Communications Conference (IPCCC-97), pp. 10–16, 1997.Google Scholar
  6. 6.
    H. Akatsuka and S. Imai. Road signposts recognition system. In Proc. SAE vehicle highway infrastructure: safety compatibility, pages 189–196, 1987.Google Scholar
  7. 7.
    N. Kehtarnavaz, N. Griswold, and D. Kang. Stop-sign recognition based on color shape processing. In Machine Vision and Applications, volume 6, pages 206–208, 1993.CrossRefGoogle Scholar
  8. 8.
    L. Priese, J. Klieber, R. Lakmann, V. Rehrmann, and R. Schian. New results on traffic sign recognition. In IEEE Proc. Intelligent Vehicles’ 94 Symposium, pages 249–253, 1994.Google Scholar
  9. 9.
    L. Priese and V. Rehrmann. On hierarchical color segmentation and applications. In Proc. CVPR, pages 633–634, 1993.Google Scholar
  10. 10.
    G. Piccioli, E. D. Michelli, and M. Campani. A robust method for road sign detection and recognition. In Proc. European Conference on Computer Vision, pages 495–500, 1994.Google Scholar
  11. 11.
    G. Piccioli, E. D. Michelli, P. Parodi, and M. Campani. Robust road sign detection and recognition from image sequences. In Proc. Intelligent Vehicles’94, pages 278–283, 1994.Google Scholar
  12. 12.
    G. Nicchiotti, E. Ottaviani, P. Castello, and G. Piccioli. Automatic road sign detection and classification from color image sequences. In S. Impedovo, editor, Proc. 7th Int. Conf. On Image Analysis and Processing, pages 623–626, 1994.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Salvatore Vitabile
    • 1
  • Antonio Gentile
    • 2
  • G. B. Dammone
    • 2
  • Filippo Sorbello
    • 2
  1. 1.CEntro di studio sulle Reti di ElaboratoriItalian National Research CouncilPalermoItaly
  2. 2.Dipartimento di ingegneria INFOrmaticaUniversity of PalermoItaly

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