Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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A Study on Modified Mask for Edge Detection in AWGN Environment

AWGN 환경에서 에지 검출을 위한 변형된 마스크에 관한 연구

  • Lee, Chang-Young (Dept. of Control and Instrumentation Eng., Pukyong National University) ;
  • Kim, Nam-Ho (Dept. of Control and Instrumentation Eng., Pukyong National University)
  • Received : 2013.05.29
  • Accepted : 2013.08.26
  • Published : 2013.09.30
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Abstract

In modern society the image processing has been applied to various digital devices such as smartphone, digital camera, and digital TV. In the field of image processing the edge detection is one of the important parts in the image processing procedure. The image edge means point that the pixel value is changed between background and object rapidly, and includes the important information such as magnitude, location, and orientation. The performance of the existing edge detection method is insufficient for the image degraded by AWGN(additive white Gaussian noise) because it detects edges by using small weighted masks. Therefore, in this paper, to detect edge in AWGN environment effectively, we proposed an algorithm that detects edge as calculated gradient of sorting vector which is transformed by estimated mask from new pixel according to each region.

현대사회에서 영상처리는 스마트폰, 디지털 카메라, 디지털 TV 등의 여러 디지털 기기에 응용되고 있다. 영상처리 분야 중에서 에지 검출은 영상처리과정에 중요한 부분이다. 영상 에지는 배경과 물체 사이에서 화소값이 급격히 변화하는 지점이며, 크기, 위치, 방향 등의 중요한 정보를 포함한다. 기존의 에지 검출 방법은 크기가 작은 가중치 마스크를 이용하여 에지를 검출하기 때문에, AWGN(additive white Gaussian noise)에 훼손된 영상의 에지 검출 결과가 다소 미흡하다. 따라서 본 연구에서는 AWGN 환경에서 효과적으로 에지를 검출하기 위해, 마스크 영역의 범위를 넓혀 각 영역에 따른 새로운 화소를 추정한 후, 추정된 마스크를 벡터로 변환하여 정렬한 후 계산된 기울기로 에지를 검출하는 알고리즘을 제안하였다.

Keywords

References

  1. R. Nevatia, "Evaluation of simplified Hueckel edge-line detector", Comput., Graph., Image Process., vol. 6, no. 6, pp. 582-588, 1977. https://doi.org/10.1016/S0146-664X(77)80017-8
  2. S. Zheng, J. Liu, J. W. Tian, "A new efficient SVM based edge detection method", Pattern Recognition Lett., Vol. 25, No. 10, pp. 1143-1154, 2004. https://doi.org/10.1016/j.patrec.2004.03.009
  3. L. R. Liang, C. G. Looney, "Competitive fuzzy edge detection", Applied Soft Computing, Vol. 3, No. 2, pp. 123-137, 2003. https://doi.org/10.1016/S1568-4946(03)00008-5
  4. Mingxiu Lin, Shuai Chen, "A new prediction method for edge detection based on human visual feature," Control and Decision Conference, 2012 24th Chinese, pp. 1465-1468, 2012.
  5. J. Canny, "A computational approach to edge detection", IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, pp. 679-698, 1986.
  6. Hu Qing-hui, Liu Xiao-gang, "The Research of An Improved Roberts Algorithm Used In Welding Line Identification", CAID & CD 2009. IEEE 10th International Conference on , pp. 786-788, 2009.
  7. Rana Abdul Rahman Lateef, "Expansion and Implementation of a 3x3 Sobel and Prewitt Edge Detection Filter to a 5x5 Dimension Filter", Baghdad College of Economic sciences University, pp. 336-348, Vol., issue 18, 2008.
  8. Amarunnishad T.M., Govindan V.K., Mathew, A.T., "Fuzzy Complement Edge Operator", ICACC, pp. 344-348, 2006.
  9. Mahdi Setayesh, Mengjie Zhang and Mark Johnston, "Improving Edge Detection Using Particle Swarm Optimisation", Image and Vision Computing New Zealand 25th International Conference of, pp. 1-8, 2011.
  10. Chang-Gi Moon and Chul-Soo Ye, "An Evauation and Combination of Noise Reduction Filtering and Edge Detection Filtering for the Feature Element Selection in Stereo Matching", Korean Journal of Remote Sensing, vol. 23, no. 4, pp. 273-285, 2007. https://doi.org/10.7780/kjrs.2007.23.4.273