doi: 10.7763/IJAPM.2012.V2.51
A Comparison of Root Mean Square Errors on Skeletonization Methods
- 1 Computer Science and Applications, M.L.N.College Yamuna Nagar.
- 2 Mathematics, J.V.Jain College Saharnpur, India.
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.
Keywords
- Vectorization
- skeletonization
- mathematical morphology
- voronoi diagram
- thinning
- zhang-suen’s algorithm
- holt’s staircase removal algorithm
- matlab
- mean
- standard deviation
- root mean square error
How to 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. 44-48, 2012. https://doi.org/ 10.7763/IJAPM.2012.V2.51
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).