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An FPGA Implementation for Texture Analysis Considering the Real-Time Requirements of Vision-Based Systems

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6578))

Abstract

This article presents an architecture based on FPGA for the calculation of texture attributes using an adequacy of the technique of sum and differences of histograms. The attributes calculated by this architecture will be used in a process of classification for identification of objects during the navigation of an autonomous robot of service. Because of that, the constraint of real-time execution plays an essential role during the architecture design. So, the architecture is designed to calculate 30 dense images with 6 different attributes of texture for 10 different displacements. Exploiting the reuse of operations in parallel on the FPGA and taking into account the requisites in the time of calculation, it is possible to use the resources in an efficient and optimised way in order to obtain an architecture with the best trade off between resources and the time of calculation. Thanks to the high performance of this architecture, it can be used in applications like medical diagnosis or target detection.

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References

  1. Avina-Cervantes, J., Estudillo-Ayala, M., Ledesma-Orozco, S., Ibarra-Manzano, M.: Boosting for image interpretation by using natural features. In: Seventh Mexican International Conference on Artificial Intelligence, MICAI 2008. pp. 117 –122 (October 2008)

    Google Scholar 

  2. Haralick, R.: Statistical and structural approaches to texture. Proceedings of the IEEE 67(5), 786–804 (1979)

    Article  Google Scholar 

  3. Ibarra-Manzano, M.A., Almanza-Ojeda, D.L., Lopez-Hernandez, J.M.: Design and optimization of real-time texture analysis using sum and difference histograms implemented on an fpga. In: Electronics, Robotics and Automotive Mechanics Conference, pp. 325–330 (2010)

    Google Scholar 

  4. Ibarra-Manzano, M., Almanza-Ojeda, D.L., Devy, M., Boizard, J.L., Fourniols, J.Y.: Stereo vision algorithm implementation in fpga using census transform for effective resource optimization. In: 12th Euromicro Conference on Digital System Design, Architectures, Methods and Tools, DSD 2009, pp. 799–805 (August 2009)

    Google Scholar 

  5. Ibarra-Manzano, M.A., Devy, M., Boizard, J.L.: Real-time classification based on color and texture attributes on an fpga-based architecture. In: Ahonen, T. (ed.) Conference on Design and Architectures for Signal and Image Processing, DASIP 2010, October 26-28, pp. 53–60. ECSI - Electronic Chip and Systems design Initiative and IEEE, Playfair Library Hall, Old College, University of Edinburgh, South Bridge, Edinburgh, Scotland, United Kingdom (2010)

    Google Scholar 

  6. Ibarra Pico, F., Cuenca Asensi, S., Corcoles, V.: Accelerating statistical texture analysis with an fpga-dsp hybrid architecture. In: FCCM 2001: Proceedings of the the 9th Annual IEEE Symposium on Field-Programmable Custom Computing Machines, pp. 289–290. IEEE Computer Society, Washington, DC (2001)

    Google Scholar 

  7. Maroulis, D., Iakovidis, D.K., Bariamis, D.: Fpga-based system for real-time video texture analysis. J. Signal Process. Syst. 53(3), 419–433 (2008)

    Article  Google Scholar 

  8. Siéler, L., Tanougast, C., Bouridane, A.: A scalable and embedded fpga architecture for efficient computation of grey level co-occurrence matrices and haralick textures features. Microprocess. Microsyst. 34(1), 14–24 (2010)

    Article  Google Scholar 

  9. Tahir, M.A., Bouridane, A., Kurugollu, F.: An fpga based coprocessor for glcmand haralick texture features and their application in prostate cancer classication. Analog Integr. Circuits Signal Process 43(2), 205–215 (2005)

    Article  Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Ibarra-Manzano, MA., Almanza-Ojeda, DL. (2011). An FPGA Implementation for Texture Analysis Considering the Real-Time Requirements of Vision-Based Systems. In: Koch, A., Krishnamurthy, R., McAllister, J., Woods, R., El-Ghazawi, T. (eds) Reconfigurable Computing: Architectures, Tools and Applications. ARC 2011. Lecture Notes in Computer Science, vol 6578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19475-7_13

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  • DOI: https://doi.org/10.1007/978-3-642-19475-7_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19474-0

  • Online ISBN: 978-3-642-19475-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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