IMAGE CONTOUR SEGMENTATION IN HARDWARE

Authors

  • Dimitrios Amanatidis Technological Educational Institute of Western Macedonia, Kastoria, Greece, Greece
  • Michael Dossis Technological Educational Institute of Western Macedonia, Kastoria, Greece, Greece
  • Iosif Androulidakis University of Ioannina, Ioannina, Greece, Greece

DOI:

https://doi.org/10.15588/1607-3274-2015-4-10

Keywords:

Image Contour Segmentation, High Level Synthesis, Custom Coprocessors Compilation, FPGA Implementation.

Abstract

The use of Behavioural Synthesis for hardware generation of a contour-based image segmentation method is considered. The segmentation
method chosen, is a well-known, state-of-the-art, robust, efficient and fast-converging one, that combines functionals depending on the curve geometry and image properties in a level-set framework. The cost function sought to be minimized, is formulated as a weighted sum of three integral measures; a robust alignment term that leads the evolving surface to the edges of the desired object, a minimal variance term that measures the homogeneity inside and outside the object, and a geodesic active surface term that is used mainly for regularization. The algorithm is initially implemented in MatLab and ADA and subsequently, it is ported to our Behavioural Synthesis tool, the CCC HLS framework, which is capable of delivering correct-by-construction RTL VHDL implementations of computation-intensive applications. This way, behavioural ADA specifications are transformed into RTL micro-architectures which then can be easily implemented by commercial RTL synthesizers.

References

Aubert G. Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations / G. Aubert and P. Kornprobst // Applied Mathematical Sciences. – Springer Science and Business Media, LLC, 2nd ed. – 2006. –Vol. 147. 2. Haralic R. Computer and Robot Vision / R. Haralic and L. Shapiro, Eds. – 1993, chapter 16, Addison-Wesley. 3. Mumford D. Boundary detection by minimizing functionals / D. Mumford, J. Shah // Proc. of the IEEE Conference on Computer Vision and Pattern Recognition. – San Francisco, CA, June 1985. – P. 22–26. 4. Marr D. Theory of edge detection / D. Marr, E. Hildreth // Proc of the Royal Society. – London B, 207. –1980. – P. 187–217. 5. Kass M. Snakes: Active contour models / M. Kass, A. Witkin, D. Terzopoulos // Int. Journal of Computer Vision. – 1988. – Vol. 1. – P. 321–331. 6. Malladi R. Shape modeling with front propagation: A level set approach // IEEE Transactions Pattern Analysis and Machine Intelligence. – 1995. – vol. 17. – P. 158 –175. 7. Caselles V. A geometric model for active contours in image processing / V. Caselles, F. Catte, T. Coll, F. Dibos // Numer. Math. – 1993. – Vol. 66. – P. 1–31. 8. Caselles V. On geodesic active contours / V. Caselles, R. Kimmel and G. Sapiro // Int. Journal of Computer Vision. – 1997. – Vol. 22, No. 1. – P. 61–79. 9. Kimmel R. Fast edge integration // Geometric Level Set Methods in Imaging, Vision and Graphics / R. Kimmel, S. Osher and N. Paragios, Eds. – New York : Springer-Verlag, 2003. 10. Segmentation of Thin Structures in Volumetric Medical Images / M. Holtzman-Gazit, R. Kimmel, N. Peled and D. Goldsher // IEEE Transactions On Image Processing. – 2006. –Vol. 15, No. 2. 11. Chan T. Active Contours Without Edges / T. Chan and L. Vese / / IEEE Transactions on Image Processing. – 2001. – Vol. 10, No. 2. – P. 266–277. 12. Osher S. Fronts Propagating with Curvature-Dependent Speed: Algorithms Based on Hamilton-Jacobi Formulations / S. Osher, J. A. Sethian // Journal of Computational Physics. – 1988. – Vol. 79 – P. 12–49. 13. Dossis M. Using Behavioural Synthesis for hardware generation of a contour-based image segmentation algorithm / M. Dossis, D. Amanatidis, I. Androulidakis // Proceedings of the International Conference on Information and Digital Technologies (IDT). – Zilina, Slovakia, July 7–9, 2015.

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Published

2015-05-16

How to Cite

Amanatidis, D., Dossis, M., & Androulidakis, I. (2015). IMAGE CONTOUR SEGMENTATION IN HARDWARE. Radio Electronics, Computer Science, Control, (4). https://doi.org/10.15588/1607-3274-2015-4-10

Issue

No. 4 (2015): Radio Electronics, Computer Science, Control

Section

Progressive information technologies

License

Copyright (c) 2016 Dimitrios Amanatidis, Michael Dossis, Iosif Androulidakis

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