Intelligent Approaches for Vectorizing Image Outlines

Affiliation(s)

Department of Information Science, Kuwait University, Adailiya Campus, P.O. Box 5969, Safat 13060, Kuwait.

Department of Information Science, Kuwait University, Adailiya Campus, P.O. Box 5969, Safat 13060, Kuwait.

ABSTRACT

Two computing approaches, based on linear and conic splines, are proposed here in reviewed and extended for vectorizing image outlines. Both of the approaches have various phases including extracting outlines of images, detecting corner points from the detected outlines, and curve fitting. Interpolation splines are the bases of the two approached. Linear spline approach is straight forward as it does not have a degree of freedom.in terms of some shape controller in its description. However, the idea of the soft computing approach, namely simulated annealing, has been utilized for conic splines. This idea has been incorporated to optimize the shape parameters in the description of the generalized conic spline. Both of the linear and conic approaches ultimately produce optimal results for the approximate vectorization of the digital contours obtained from the generic shapes.

Two computing approaches, based on linear and conic splines, are proposed here in reviewed and extended for vectorizing image outlines. Both of the approaches have various phases including extracting outlines of images, detecting corner points from the detected outlines, and curve fitting. Interpolation splines are the bases of the two approached. Linear spline approach is straight forward as it does not have a degree of freedom.in terms of some shape controller in its description. However, the idea of the soft computing approach, namely simulated annealing, has been utilized for conic splines. This idea has been incorporated to optimize the shape parameters in the description of the generalized conic spline. Both of the linear and conic approaches ultimately produce optimal results for the approximate vectorization of the digital contours obtained from the generic shapes.

Cite this paper

M. Sarfraz, "Intelligent Approaches for Vectorizing Image Outlines,"*Journal of Software Engineering and Applications*, Vol. 5 No. 12, 2012, pp. 78-83. doi: 10.4236/jsea.2012.512B016.

M. Sarfraz, "Intelligent Approaches for Vectorizing Image Outlines,"

References

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[2] A. A. Goshtasby, “Grouping and Pa-rameterizing Irregularly Spaced Points for Curve Fitting”, ACM Transactions on Graphics, Vol. 19, No. 3, 2000, pp. 185-203.

[3] P. Reche, C. Urdiales, A. Bandera,C. Trazegnies, F. Sandoval, “Corner Detection by Means of Contour Local Vectors”, Electronic Letters, Vol. 38, No. 14, 2002.

[4] M. Marji, P. Siv, “A New Algorithm for Dominant Points Detection and Polygonization of Digital Curves”, Pattern Recognition, 2003, pp. 2239-2251.

[5] Wu-Chih Hu, “Multiprimitive Seg-mentation Based on Meaningful Breakpoints for Fitting Digital Planar Curves with Line Segments and Conic Arcs”, Image and Vision Computing, 2005, pp. 783-789.

[6] H. Freeman, L. S. Davis, “A corner find-ing algorithm for chain-coded curves”, IEEE Trans. Computers, Vol. 26, 1977, pp. 297-303.

[7] N. Richard, T. Gilbert, “Extraction of Dominant Points by estima-tion of the contour fluctuations”, Pattern Recognition, Vol. 35, 2002, pp. 1447-1462.

[8] M. Sarfraz, “Representing Shapes by Fitting Data using an Evolu-tionary Approach”, International Journal of Comput-er-Aided Design & Applications, Vol. 1, No. 1-4, 2004, pp 179-186.

[9] M. Sarfraz, M. A. Khan, “An Auto-matic Algorithm for Approximating Boundary of Bitmap Characters”, Future Generation Computer Systems, 2004, pp. 1327-1336.

[10] M. Sarfraz, “Some Algorithms for Curve Design and Automatic Outline Capturing of Images”, International Journal of Image and Graphics, 2004, pp. 301-324.

[11] Z. J. Hou, G. W. Wei, “A New Approach to Edge Detection”, Pattern Recognition, 2002, pp. 1559-1570.

[12] M. Sarfraz, “Computer-Aided Reverse Engineering using Simulated Evolution on NURBS”, International Journal of Virtual & Physical Prototyping, Vol. 1, No. 4, 2006, pp. 243 – 257.

[13] M. Sarfraz, M. Riyazuddin, M. H. Baig, “Capturing Planar Shapes by Approximating their Outlines, International Journal of Computational and Applied Mathematics, Vol. 189, No. 1-2, 2006, pp. 494 – 512.

[14] M. Sarfraz, A. Rasheed, “A Randomized Knot Insertion Algorithm for Outline Capture of Planar Images using Cubic Spline”, The Proceedings of The 22th ACM Symposium on Applied Computing (ACM SAC-07), Seoul, Korea, 2007, pp. 71 – 75.

[15] H. Kano, H. Nakata, C. F. Martin, “Optimal Curve Fitting and Smoothing using Normalized Uniform B-Splines: A Tool for Studying Complex Systems”, Applied Mathematics and Computation, 2005, pp. 96-128.

[16] Z. Yang, J. Deng, F. Chen, “Fitting Unorganized Point Clouds with Active Implicit Spline Curves”, B- Visual Computer, 2005, pp. 831-839.

[17] G. Lavoue, F. Dupont, A. Baskurt, “A New Subdivision Based Approach for Piecewise Smooth Approximation of 3D Polygonal Curves”, Pattern Recognition, Vol. 38, 2005, pp. 1139-1151.

[18] H. Yang, W. Wang, J. Sun, “Control Point Adjustment for B-Spline Curve Approximation”, Computer Aided Design, Vol. 36, 2004, pp. 639-652.

[19] J. H. Horng, “An Adaptive Smoothing Approach for Fitting Digital Planar Curves with Line Segments and Circular Arcs”, Pattern Recognition Letters, Vol. 24, No. 1-3, 2003, pp. 565-577.

[20] B. Sarkar, L. K. Singh, D. Sarkar, “Approximation of Digital Curves with Line Segments and Circular Arcs using Genetic Algorithms”, Pattern Recognition Letters, Vol. 24, 2003, pp. 2585-2595.

[21] X. Yang, “Curve Fitting and Fairing using Conic Spines”, Computer Aided Design, Vol. 6, No. 5, 2004, pp. 461-472.

[22] X. N. Yang, G. Z. Wang “Planar Point Set Fairing and Fitting by Arc Splines”, Computer Aided Design, 2001, pp. 35-43.

[23] M. Sarfraz, “Designing Objects with a Spline”, International Journal of Computer Mathematics, Vol. 85, No. 7, 2008.

[24] S. Kirkpatrick, C. D. Gelatt Jr., M. P. Vecchi, "Optimization by Simulated Annealing", Science, Vol. 220, No 4598, 1983, pp. 671-680.

[25] R. C. Gonzalez, R. E. Woods, S. L. Eddins, “Digital Image Processing Using MATLAB”, 2nd Ed., 2009, Gatesmark Publishing.

[26] M. S. Nixon, A.S. Aguado, “Feature extraction and image processing”, 2008, Elsevier.

[27] M. Sarfraz, “Outline Capture of Images by Multilevel Coordinate Search on Cubic Splines”, Lecture Notes in Artificial Intelligence, A. Ni-cholson and X. Li (Eds.): LNAI 5866, Springer-Verlag Berlin Heidelberg, 2009, pp. 636–645.

[28] M. Sarfraz, “Vectorizing Outlines of Generic Shapes by Cubic Spline using Simulated Annealing”, International Journal of Computer Mathematics, Vol. 87, No. 8, 2010, pp. 1736 – 1751.

[29] Sarfraz, M. (2011), Capturing Image Outlines using Simulated Annealing Approach with Conic Splines,The Proceedings of The International Conference on Information and Intelligent Computing (ICIIC 2011), Hong Kong, China, November 25-27, 2011, IPCSIT Vol. 18, pp. 152 – 157, IASCIT Press Singapore.

[30] M. Sarfraz, “Vectorizing Image Outlines using Spline Computing Approach”, The Proceedings of The 4th International Conference on Machine Learning and Computing (ICMLC 2012), Hong Kong, China, 2012, ASME Press.

[1] D. Chetrikov, S. Zsabo, “A Simple and Efficient Algo-rithm for Detection of High Curvature Points in Planar Curves”, Proceedings of the 23rd Workshop of the Aus-tralian Pattern Recognition Group, 1999, pp. 1751-2184.

[2] A. A. Goshtasby, “Grouping and Pa-rameterizing Irregularly Spaced Points for Curve Fitting”, ACM Transactions on Graphics, Vol. 19, No. 3, 2000, pp. 185-203.

[3] P. Reche, C. Urdiales, A. Bandera,C. Trazegnies, F. Sandoval, “Corner Detection by Means of Contour Local Vectors”, Electronic Letters, Vol. 38, No. 14, 2002.

[4] M. Marji, P. Siv, “A New Algorithm for Dominant Points Detection and Polygonization of Digital Curves”, Pattern Recognition, 2003, pp. 2239-2251.

[5] Wu-Chih Hu, “Multiprimitive Seg-mentation Based on Meaningful Breakpoints for Fitting Digital Planar Curves with Line Segments and Conic Arcs”, Image and Vision Computing, 2005, pp. 783-789.

[6] H. Freeman, L. S. Davis, “A corner find-ing algorithm for chain-coded curves”, IEEE Trans. Computers, Vol. 26, 1977, pp. 297-303.

[7] N. Richard, T. Gilbert, “Extraction of Dominant Points by estima-tion of the contour fluctuations”, Pattern Recognition, Vol. 35, 2002, pp. 1447-1462.

[8] M. Sarfraz, “Representing Shapes by Fitting Data using an Evolu-tionary Approach”, International Journal of Comput-er-Aided Design & Applications, Vol. 1, No. 1-4, 2004, pp 179-186.

[9] M. Sarfraz, M. A. Khan, “An Auto-matic Algorithm for Approximating Boundary of Bitmap Characters”, Future Generation Computer Systems, 2004, pp. 1327-1336.

[10] M. Sarfraz, “Some Algorithms for Curve Design and Automatic Outline Capturing of Images”, International Journal of Image and Graphics, 2004, pp. 301-324.

[11] Z. J. Hou, G. W. Wei, “A New Approach to Edge Detection”, Pattern Recognition, 2002, pp. 1559-1570.

[12] M. Sarfraz, “Computer-Aided Reverse Engineering using Simulated Evolution on NURBS”, International Journal of Virtual & Physical Prototyping, Vol. 1, No. 4, 2006, pp. 243 – 257.

[13] M. Sarfraz, M. Riyazuddin, M. H. Baig, “Capturing Planar Shapes by Approximating their Outlines, International Journal of Computational and Applied Mathematics, Vol. 189, No. 1-2, 2006, pp. 494 – 512.

[14] M. Sarfraz, A. Rasheed, “A Randomized Knot Insertion Algorithm for Outline Capture of Planar Images using Cubic Spline”, The Proceedings of The 22th ACM Symposium on Applied Computing (ACM SAC-07), Seoul, Korea, 2007, pp. 71 – 75.

[15] H. Kano, H. Nakata, C. F. Martin, “Optimal Curve Fitting and Smoothing using Normalized Uniform B-Splines: A Tool for Studying Complex Systems”, Applied Mathematics and Computation, 2005, pp. 96-128.

[16] Z. Yang, J. Deng, F. Chen, “Fitting Unorganized Point Clouds with Active Implicit Spline Curves”, B- Visual Computer, 2005, pp. 831-839.

[17] G. Lavoue, F. Dupont, A. Baskurt, “A New Subdivision Based Approach for Piecewise Smooth Approximation of 3D Polygonal Curves”, Pattern Recognition, Vol. 38, 2005, pp. 1139-1151.

[18] H. Yang, W. Wang, J. Sun, “Control Point Adjustment for B-Spline Curve Approximation”, Computer Aided Design, Vol. 36, 2004, pp. 639-652.

[19] J. H. Horng, “An Adaptive Smoothing Approach for Fitting Digital Planar Curves with Line Segments and Circular Arcs”, Pattern Recognition Letters, Vol. 24, No. 1-3, 2003, pp. 565-577.

[20] B. Sarkar, L. K. Singh, D. Sarkar, “Approximation of Digital Curves with Line Segments and Circular Arcs using Genetic Algorithms”, Pattern Recognition Letters, Vol. 24, 2003, pp. 2585-2595.

[21] X. Yang, “Curve Fitting and Fairing using Conic Spines”, Computer Aided Design, Vol. 6, No. 5, 2004, pp. 461-472.

[22] X. N. Yang, G. Z. Wang “Planar Point Set Fairing and Fitting by Arc Splines”, Computer Aided Design, 2001, pp. 35-43.

[23] M. Sarfraz, “Designing Objects with a Spline”, International Journal of Computer Mathematics, Vol. 85, No. 7, 2008.

[24] S. Kirkpatrick, C. D. Gelatt Jr., M. P. Vecchi, "Optimization by Simulated Annealing", Science, Vol. 220, No 4598, 1983, pp. 671-680.

[25] R. C. Gonzalez, R. E. Woods, S. L. Eddins, “Digital Image Processing Using MATLAB”, 2nd Ed., 2009, Gatesmark Publishing.

[26] M. S. Nixon, A.S. Aguado, “Feature extraction and image processing”, 2008, Elsevier.

[27] M. Sarfraz, “Outline Capture of Images by Multilevel Coordinate Search on Cubic Splines”, Lecture Notes in Artificial Intelligence, A. Ni-cholson and X. Li (Eds.): LNAI 5866, Springer-Verlag Berlin Heidelberg, 2009, pp. 636–645.

[28] M. Sarfraz, “Vectorizing Outlines of Generic Shapes by Cubic Spline using Simulated Annealing”, International Journal of Computer Mathematics, Vol. 87, No. 8, 2010, pp. 1736 – 1751.

[29] Sarfraz, M. (2011), Capturing Image Outlines using Simulated Annealing Approach with Conic Splines,The Proceedings of The International Conference on Information and Intelligent Computing (ICIIC 2011), Hong Kong, China, November 25-27, 2011, IPCSIT Vol. 18, pp. 152 – 157, IASCIT Press Singapore.

[30] M. Sarfraz, “Vectorizing Image Outlines using Spline Computing Approach”, The Proceedings of The 4th International Conference on Machine Learning and Computing (ICMLC 2012), Hong Kong, China, 2012, ASME Press.