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Reseach Article

A Review on Emboss and Deboss Features of Edge Matching

by Kajal A. Prajapati, Sanjay M. Shah
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 162 - Number 4
Year of Publication: 2017
Authors: Kajal A. Prajapati, Sanjay M. Shah
10.5120/ijca2017913275

Kajal A. Prajapati, Sanjay M. Shah . A Review on Emboss and Deboss Features of Edge Matching. International Journal of Computer Applications. 162, 4 ( Mar 2017), 22-26. DOI=10.5120/ijca2017913275

@article{ 10.5120/ijca2017913275,
author = { Kajal A. Prajapati, Sanjay M. Shah },
title = { A Review on Emboss and Deboss Features of Edge Matching },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2017 },
volume = { 162 },
number = { 4 },
month = { Mar },
year = { 2017 },
issn = { 0975-8887 },
pages = { 22-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume162/number4/27232-2017913275/ },
doi = { 10.5120/ijca2017913275 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:08:05.207780+05:30
%A Kajal A. Prajapati
%A Sanjay M. Shah
%T A Review on Emboss and Deboss Features of Edge Matching
%J International Journal of Computer Applications
%@ 0975-8887
%V 162
%N 4
%P 22-26
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Matching of the product is an importanat problem in the production industry to maintain the quality control. Emboss and Deboss are the processes of creating both raised or recessed relief images and designs in paper and other materials. An embossed pattern is raised against the background, while a debossed pattern is sunken into the surface of the material. Every Emboss or Deboss object has inner and outer boundary of the object, which may be shaped or unshaped. Therefore, the object’s boundary is detected by Edge Detection using different operators like Canny, Sobel, Log, Prewitt etc. Till now, various methods available in the market are only matching objects which are following straight line and some particular shapes, i.e. square, rectangle, circle etc. So, researchers have proposed modification or investigation for Edge matching to make it proper for practical applications of unstructured shape. For Edge Matching, different similarity measures such as the Straight Line Matching Algorithm and Corner detection are used. But when the query image is unstructured, these techniques fail. In this paper, we surveyed various Edge Detection and Edge Matching techniques.

References
  1. P. Kaur and B. Kaur, “2-D Geometric Shape Recognition Using Canny Edge Detection Technique,” 2016 Int. Conf. Comput. Sustain. Glob. Dev., pp. 3161–3164, 2016.
  2. S. Guiming and S. Jidong, “Remote Sensing Image Edge-Detection Based on Improved Canny Operator,” 2016 8th IEEE Int. Conf. Commun. Softw. Networks, pp. 652–656, 2016.
  3. L. Yuan and X. Xu, “Adaptive Image Edge Detection Algorithm Based on Canny Operator,” 2015 4th Int. Conf. Adv. Inf. Technol. Sens. Appl., no. 2, pp. 28–31, 2015.
  4. L. Zhang, Y. Sun, and F. Chen, “An Improved Edge Detection Algorithm Based on Fuzzy Theory,” 2015 12th Int. Conf. Fuzzy Syst. Knowl. Discov., pp. 380–384, 2015.
  5. W. Zhang, D. Shi, and X. Yang, “An Improved Edge Detection Algorithm Based on Mathematical Morphology and Directional Wavelet Transform,” 2015 8th Int. Congr. Image Signal Process. (CISP 2015), no. Cisp, pp. 335–339, 2015.
  6. S. Tabbone and D. Ziou, “Edge Detection Techniques - An Overview,” Int. J. Pattern Recognit. Image Anal., vol. 8, pp. 537–559, 1998.
  7. V. Ferrari, L. Fevrier, C. Schmid, and S. Member, “Groups of Adjacent Contour Segments for Object Detection,” IEEE Trans. PATTERN Anal. Mach. Intell., vol. 30, no. 1, pp. 36–51, 2008.
  8. P. Doll and C. L. Zitnick, “Structured Forests for Fast Edge Detection,” ICCV, 2013.
  9. J. Malik, S. Belongie, T. Leung, and J. Shi, “Contour and Texture Analysis for Image Segmentation,” Int. J. Comput. Vis., vol. 43, no. 1, pp. 7–27, 2001.
  10. P. Arbelaez, M. Maire, C. Fowlkes, and J. Malik, “Contour Detection and Hierarchical Image Segmentation,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 5, pp. 898–916, 2011.
  11. S. Sukprasertchai and T. Suesut, “Real-time Surface Acquisition of Tire Sidewall for Reading Embossed Information,” Proc. Int. MultiConference Eng. Comput. Sci., vol. I, pp. 16–19, 2016.
  12. S. Israni and S. Jain, “EDGE DETECTION OF LICENSE PLATE USING SOBEL OPERATOR,” Int. Conf. Electr. Electron. Optim. Tech., pp. 3561–3563, 2016.
  13. G. Yang and F. Xu, “Procedia Engineering Research and analysis of Image edge detection algorithm Based on the MATLAB,” Publ. by Elsevier Ltd., 2011.
  14. S. Wang and J. Zhao, “A Self-Adaptive Edge Detection Method Based on LoG Algorithm,” ICALIP, vol. 2, no. 1, pp. 1009–1011, 2008.
  15. J. Kaur, “Review Paper on Edge Detection Techniques in Digital Image Processing,” Int. J. Innov. Adv. Comput. Sci., vol. 5, no. 11, pp. 11–14, 2016.
  16. S. K. Vishwakarma, D. S. Yadav, and Akash, “Analysis of Lane Detection Techniques using openCV,” IEEE INDICON, pp. 1–4, 2015.
  17. K. Patoommakesorn, F. Vignat, and F. Villeneuve, “A New Straight Line Matching Technique by Integration of Vision-based Image Processing,” Procedia CIRP, vol. 41, pp. 777–782, 2016.
  18. Y. Herdiyeni, D. I. Lubis, and S. Douady, “Leaf Shap pe Identification of Medicinal Leaves using g Curvilinear Shape Descriptor,” 2015 Seventh Int. Conf. Soft Comput. Pattern Recognit. (SoCPaR 2015), pp. 218–223, 2015.
  19. H. Alt, B. Behrends, and J. Blomer, “Approximate Matching of Polyogonal Shapes,” Ann. Math. Artif. Intell., vol. 13, no. 7141, pp. 251–265, 1993.
  20. H. Alt and M. GODAU, “Computing the Fréchet distance between two polygonal curves,” Int. J. Comput. Geom. Appl., vol. 5, pp. 75–91, 1995.
  21. H. Alt and L. Scharf, “Shape matching by random sampling,” Theor. Comput. Sci., vol. 442, pp. 2–12, 2012.
  22. A. Efrat, Q. Fan, and S. Venkatasubramanian, “Curve matching, time warping, and light fields: New algorithms for computing similarity between curves,” J. Math. Imaging Vis., vol. 27, no. 3, pp. 203–216, 2007.
  23. W. Peng, X. Hongling, L. Wenlin, and S. Wenlong, “Harris Scale Invariant Corner Detection Algorithm Based on the,” Int. J. Signal Process. Image Process. Pattern Recognit., vol. 9, no. 3, pp. 413–420, 2016.
  24. G. Borgefors, “Hierarchical Chamfer matching: A parametric edge matching algorithm,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, no. 6. pp. 849–865, 1988.
  25. J. Flusser, “Moment Invariants in Image Analysis,” Int. Sch. Sci. Res. Innov., vol. 1, no. 11, pp. 3708–3713, 2007.
  26. W. Wang, A. Lou, and J. Wang, “the Research of Line Matching Algorithm Under the Improved,” Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., vol. XXXIX, no. September, pp. 345–350, 2012.
  27. T. Xiang, G. Xia, and L. Zhang, “Image stitching with perspective-preserving warping,” vol. III, no. July, pp. 12–19, 2016.
  28. S. Belongie, J. Malik, and J. Puzicha, “Shape Matching and Object Recognition Using Shape Contexts,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 24, pp. 509–522, 2002.
  29. S. Wei, L. Na, S. Lijuan, S. Shulin, and L. Xiangpeng, “Two improved methods of SIFT algorithm combined with Harris,” Proc. 2012 24th Chinese Control Decis. Conf. CCDC 2012, pp. 3251–3254, 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Edge Detection Contour Tracking Edge Matching