A New Method for Contour Approximation Using Basic Ramer Idea

Authors: Ali Abdrhman Ukasha

Abstract:

This paper presented two new efficient algorithms for contour approximation. The proposed algorithm is compared with Ramer (good quality), Triangle (faster) and Trapezoid (fastest) in this work; which are briefly described. Cartesian co-ordinates of an input contour are processed in such a manner that finally contours is presented by a set of selected vertices of the edge of the contour. In the paper the main idea of the analyzed procedures for contour compression is performed. For comparison, the mean square error and signal-to-noise ratio criterions are used. Computational time of analyzed methods is estimated depending on a number of numerical operations. Experimental results are obtained both in terms of image quality, compression ratios, and speed. The main advantages of the analyzed algorithm is small numbers of the arithmetic operations compared to the existing algorithms.

Keywords: Polygonal approximation, Ramer, Triangle and Trapezoid methods.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1334618

References:

[1] Dziech A., Besbas W. S., Nabout A. and Nour Eldin H. A., "Fast algorithm for closed contour extraction", Proc. of the 4th International Workshop on Systems, Signals and Image Processing, Poznań, Poland, pp. 203-206, 1997.
[2] Sklansky J. and Gonzalez V., "Fast polygonalapproximation of digitized curves", Pattern Recognition, Volume 12, Issue 5, pp. 327- 331, 1980.
[3] Ramer U., "An iterative procedure for the Polygonal approximation of plane curves", Computer Graphics and Image Processing, Academic Press, Volume 1, Issue 3, pp. 244-256, 1972.
[4] Dziech A., Ukasha A. and Baran R., "Fast method for contour approximation and compression", WSEAS Transaction on communications, Volume 5, Issue 1, pp. 49-56, 2006.
[5] Baran R., and Dziech A., "Tangent method and the other efficient methods of contour compression", WSEAS Transactions on Computers, Volume 4, Issue 7, pp. 805-813, 2005.
[6] Zhu P. and Chirlian P. M., "On critical point detection of digital shapes", IEEE Transaction on Pattern Analysis and Machine Intelligence, Volume 17, Issue 8, pp. 737-748, 1995.
[7] Batchelor B. G. and Laing S. G., "Polar-vector representations of edges in Pictures", Electronics Letters, Volume 13, Issue 24, pp. 727- 729, 1977.
[8] Jain A. K., "Fundamentals of Digital Image Processing", Englewood Cliffs, NJ: Prentice-Hall, 1989.
[9] Ukasha A., Dziech A., Elsherif E. and Baran R.,"An efficient method of contour compression",International Conference on Visualization, Imaging and Image Processing (IASTED/VIIP),Cambridge, United Kingdom, pp. 213-218, 2009.
[10] Ukasha A., Dziech A. & Baran R., "A New Method For Contour Compression", WSEAS Int. Conf. on Signal, Speech and Signal Processin (SSIP 2005), Corfu Island, Greece, pp. 282- 286, 2005.
[11] Dziech A., Baran R. & Ukasha A., "Contour compression using centroid method", WSEAS Int. Conf. on Electronics, Signal Processing and Control (ESPOCO 2005), Copacabana, Rio de Janeiro, Brazil, pp. 225-229, 2005.
[12] Ukasha A., "Arabic Letters Compression using New Algorithm of Trapezoid method", International Conference on Signal Processing, Robotics and Automation (ISPRA'10), Cambridge, United Kingdom, 336-341, 2010.
[13] Gonzalez R. C., "Digital Image Processing",Second Edition, Addison Wesley, 1987.
[14] Besbas W., "Contour Extraction, Processing and Recognition", Poznan University of Technology, Ph. D. Thesis, 1998.