Edge detection Definition, Modelling and Methodologies
International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)
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Any significant change in image pixels’ intensity can produce the edge that appears as the boundary that isolates various image regions. According to image amplitude changes, edges can be modeled into different types such as; Step, Ramp, Ridge /Line, and Roof Edges. Image edge detection techniques usually reduce the amount of information and ignore the useless data with preserving main image properties, however, Edge detection techniques are mainly grouped into two categories, Gradient and Laplacian edge detection techniques. This paper introduces different concepts related to edges, and discusses essential characteristics of various edge detection techniques.
  Monica Avlash, Lakhwinder Kaur, “Performances Analysis of Different Edge Detection Methods On Road Images”, International Journal of Advanced Research in Engineering and Applied Sciences, Vol. 2, No. 6, June 2013.
  Gonzales, R. C. and Woods, R. E., Digital Image Processing. Prentice-Hall, Upper Saddle River, NJ, 3rd edition, 2008.
  Raman Maini and Himanshu Aggarwal, “Study and Comparison of Various Image Edge Detection Techniques”, International Journal of Image Processing (IJIP), Volume (3) : Issue (1), 2009
  Noor A. Ibraheem, Mokhtar M. hasan, Shaima M., “Automatic Block Selection for Synthesizing Texture Images using Genetic Algorithms”, Baghdad Science Journal, University of Baghdad, Iraq, vol. 6(4):822-830, Dec. 2009.
  Edge Detection by Trucco, Chapter 4 and Jain ct al.,Chapter 5., website: https://www.cse.unr.edu/~bebis/CS791E/Notes/EdgeDetection.pdf
  Ireyuwa E. Igbinosa, “Comparison of Edge Detection Technique in Image Processing Techniques”, International Journal of Information Technology and Electrical Engineering, Vol. 2, No. 1, February 2013.
  G.T. Shrivakshan, “A Comparison of various Edge Detection Techniques used in Image Processing”, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 5, No 1, September 2012.
  Rashmi, Mukesh Kumar, and Rohini Saxena, “Algorithm and Technique on Various Edge Detection: A Survey”, Signal & Image Processing : An International Journal (SIPIJ), Vol.4, No.3, June 2013, DOI : 10.5121/sipij.2013.4306 65
 Mokhtar M Hasan, Pramod K Mishra, “Comparative Study for Construction Of Gesture Recognition System”, International Journal of Computer Science and Software Technology, vol. 4(1):15-21, 2011.
 Pramod K. Mishra Mokhtar M. Hasan, “Superior Skin Color Model using Multiple of Gaussian Mixture Model”, British Journal of Science, vol. 6(1):1-14, 2012.
 MM Hasan, PK Mishra, “Performance Evaluation of Modified Segmentation on Multi Block For Gesture Recognition System”, International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 4(4):17-28, 2011.
 Mokhtar M Hasan, Pramod K Mishra, “Novel algorithm for multi hand detection and geometric features extraction and recognition”, vol. 3(5):1-12, 2012.
 MM Hasan, “New Rotation Invariance Features Based on Circle Partitioning”, J Comput Eng Inf Technol 2: 2. doi: http://dx. doi. org/10.4172/2324, vol. 9307 (2). 2013.
 Mokhtar M Hasan, Pramod K Mishra, “Direction analysis algorithm using statistical approaches”, Fourth International Conference on Digital Image Processing (ICDIP 2012), doi: http://dx.doi.org/10.1117/12.946046 .
 Mokhtar M Hasan, Pramod K Misra, “Robust Gesture Recognition using Euclidian Distance”, IEEE International Conference on Computer and Computational Intelligence, 978-1.
Digital image processing, Edge detection, Gradient methods, Laplacian methods.