Abstract—Vectorization is the most fundamental operation in interpretation of line drawings and document analysis. There are several reasons for converting image vectorization. Vector data is normally created from existing natural source image like photographs, scanned images. Choosing a best vectorization method that suits the needs of the system is very important. In general, good methods must preserve information like line geometry and intersection junction as far as possible. It is also important to analyze the error and find the accuracy of the result with respect to the original data. We have compared Skeletonization by Mathematical Morphology and Voronoi Diagrams with original image for vectorizing images. Root mean squre error is one of the good methods to analysis an error on original Image, Mathematical Morphology and Voronoi Diagrams. Literature about above said methods is also included in this paper.

Index Terms—Vectorization, skeletonization, mathematical morphology, voronoi diagram, thinning, zhang-suen’s algorithm, holt’s staircase removal algorithm, matlab, mean, standard deviation, root mean square error.

N. Daryal is with Computer Science and Applications, M.L.N.College Yamuna Nagar.
V. Kumar is with Mathematics, J.V.Jain College Saharnpur, India.



Cite: Neeti Daryal and Vinod Kumar, "A Comparison of Root Mean Square Errors on Skeletonization Methods," International Journal of Applied Physics and Mathematics  vol. 2, no. 1, pp. 044-048, 2012.