CFP last date
20 May 2024
Reseach Article

Color Edge Detector with Sobel-PCA

by Hanane Rami, Mohammed Hamri, Lhoussiene Masmoudi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 75 - Number 6
Year of Publication: 2013
Authors: Hanane Rami, Mohammed Hamri, Lhoussiene Masmoudi
10.5120/13114-0448

Hanane Rami, Mohammed Hamri, Lhoussiene Masmoudi . Color Edge Detector with Sobel-PCA. International Journal of Computer Applications. 75, 6 ( August 2013), 12-16. DOI=10.5120/13114-0448

@article{ 10.5120/13114-0448,
author = { Hanane Rami, Mohammed Hamri, Lhoussiene Masmoudi },
title = { Color Edge Detector with Sobel-PCA },
journal = { International Journal of Computer Applications },
issue_date = { August 2013 },
volume = { 75 },
number = { 6 },
month = { August },
year = { 2013 },
issn = { 0975-8887 },
pages = { 12-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume75/number6/13114-0448/ },
doi = { 10.5120/13114-0448 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:43:32.159763+05:30
%A Hanane Rami
%A Mohammed Hamri
%A Lhoussiene Masmoudi
%T Color Edge Detector with Sobel-PCA
%J International Journal of Computer Applications
%@ 0975-8887
%V 75
%N 6
%P 12-16
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Edge detection is one of the most commonly used operations in computer vision, The key of edge detection is the choice of threshold; the choice of threshold directly determines the results of edge detection. How to automatically determine an optimal threshold is one of difficult points of edge detection. In this paper, Sobel edge detection operator and its improved algorithm are first discussed in term of optimal thresholding. We include color information into a color edge detection approach based on principal components analysis (PCA). Finally, the edge detection experiments of synthetic image and real color images are conducted by means of two algorithms. The comparative experiment results show that the new algorithm is very effective. The results are also better than the classical methods.

References
  1. M. B. Ahmad and T. S. Choi , Local Threshold and Boolean Function Based Edge Detection, IEEE Transactions on Consumer
  2. T. J. Yen, A qualitative pro?le-based approach to edge detection, PhD Thesis, New York University, 2003.
  3. Mark A. Ruzon Carlo Tomasi "Color Edge detection with the Compass Operator", IEEE Conference on Computer Vision and Pattern Recognition
  4. S. Baker and S. K. Nayar. Global Measures of Coherence for Edge Detector Evaluation. Conference on Comp Tavel, P. 2007 Modeling and Simulation Design. AK Peters Ltd.
  5. I. T. Jolliffe, Principal component analysis, Springer–Verlag, Heidelberg–New York, 1986.
  6. T. Carron and P. Lambert, ``Color edge detector using jointly hue, saturation and intensity,'' in Proc. IEEE International Conference on Image Processing, pp. 977-981, October 1994.
  7. Faugeras. Three-dimensional Computer Vision: A Geometric Viewpoint. MIT Press, 1993.
  8. J. Canny. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6):679–698, November 1986.
  9. R. Deriche. Fast algorithms for low-level vision. IEEE Transactions on Pattern Analysis and Machine Spector, A. Z. 1989. Achieving application requirements. In Distributed Systems, S. Mullender
  10. R. Deriche. Using Canny's criteria to derive a recursively implemented optimal edge detector. International Journal of Computer Vision, 1(2): 167–187, May 1987.
  11. P. Gouton, H. Laggoune, Rk. Kouassi, M. Paindavoine. Optimal detector for crest lines. Optical Engineering, 39(6): 1602–1611, June 2000.
  12. I. Sobel. An isotropic image gradient operator, In H. Freeman (Eds. ), Machine Vision for Three-Dimensional Scenes, pages 376–379. Academic Press, 1990.
Index Terms

Computer Science
Information Sciences

Keywords

Color Edge Detection Principal Component Analysis Sobel filter the first Global Measure of Coherence (GMC1)