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

  • 제18권8호
  • /
  • Pages.1973-1980
  • /
  • 2014
  • /
  • 2234-4772(pISSN)
  • /
  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
권호 표지
DOI QR코드

DOI QR Code

Salt & Pepper 잡음 환경에서 에지 검출 알고리즘에 관한 연구

A Study on Edge Detection Algorithm in Salt & Pepper Noise Environments

  • Lee, Chang-Young (Dept. of Control and Instrumentation Eng., Pukyong National University) ;
  • Kim, Nam-Ho (Dept. of Control and Instrumentation Eng., Pukyong National University)
  • 투고 : 2014.04.08
  • 심사 : 2014.05.12
  • 발행 : 2014.08.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

영상, 차선, 물체 인식 등을 위한 에지 검출은 중요한 영상 처리 방법이며, 이를 위한 기존의 방법에는 Sobel, Prewitt, Roberts, Laplacian, LoG(Laplacian of Gaussian) 등이 있다. 이러한 방법들은 salt & pepper 잡음에 훼손된 영상에서 특성이 미흡하다. 이와 같은 문제점을 개선하기 위하여 본 논문에서는 중심 화소의 인접 화소를 중심으로 국부 마스크를 설정하여, 그것의 중심 화소가 비잡음인 경우 그대로 처리하고 잡음인 경우 추정 마스크를 구한 후, 가중치 마스크를 적용하여 에지를 검출하는 알고리즘을 제안하였다.

Edge detection for such as image, lane and object recognition is important image processing method. And some traditional method for this, there are Sobel, Prewitt, Roberts, Laplacian, LoG(Laplacian of Gaussian) and so on. Characteristics of these methods are insufficient in the salt & pepper noise added image. In order to improve such a problem of conventional methods, in this paper, we proposed an algorithm applying the weighted mask for detecting an edge by setting the local mask centered on the adjacent of the central pixel if central pixel of the mask is non-noise, it is intactly set by element of estimated mask, after calculating estimated mask if it is noise.

키워드

참고문헌

  1. G. Economou, "Detecting edges using density value", Electronics letters, vol. 40, no. 24, pp. 1528-1530, 2004. https://doi.org/10.1049/el:20046741
  2. Sarif K. Naik, C. A. Murthy, "Standardization of Edge Magnitude in Color images", IEEE Trans. on Image Processing, vol. 15, no. 9, pp. 2588-2595, 2006. https://doi.org/10.1109/TIP.2006.877408
  3. Shun-feng Ma, Geng-feng Zheng, Long-xu Jin, Shuang-li Han, Ran-feng Zhang, "Directional Multiscale Edge Detection Using the Contourlet Transform", Advanced Computer Control, vol. 2, pp.58-62, 2010.
  4. B Kaur, A Garg, "Mathematical Morphological Edge Detection For Remote Sensing Images", Electronics Computer Technology, vol. 5, pp. 324-327, 2011.
  5. Hongyan Sun, Shuxue Tian, "Image retrieval based on blocked histogram and Sobel edge detection algorithm", International Conference on Computer Science and Service System, pp.3277-3281, 2011.
  6. Gupta K.G., Agrawal N., Maity S.K., "Performance analysis between aparapi (a parallel API) and JAVA by implementing sobel edge detection Algorithm", National Conference on Parallel Computing Technologies, pp.1-5, 2013.
  7. Hua Xiang, Bin Yan, Qiong Cai, Guangyi Zou, "An edge detection algorithm based-on Sobel operator for images captured by binocular microscope", International Conference on Electrical and Control Engineering, pp.980-982, 2011.
  8. Rosenfeld Azriel, "The Max Roberts Operator is a Hueckel-Type Edge Detector", IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.PAMI-3, no.1, pp.101-103, Jan. 1981. https://doi.org/10.1109/TPAMI.1981.4767056
  9. Snekhalatha, Anburajan M., Venkatraman,B., Menaka M., Raj B., "Evaluation of rheumatoid arthritis in small animal model using Thermal imaging", International Conference on Signal Processing, Communication, Computing and Networking Technologies, pp.785-791, 2011.
  10. Cai Lei, Zhang Ji-hua, Zhang Shi-qiang, Guan Xiao-wei, "Study on the method to process the images of the laser initiative illumination", International Conference on Image Analysis and Signal Processing, pp.1-4, 2012.
  11. Nema M.K., Rakshit S., Chaudhuri S., "Image Denoising Using Edge Model-based Representation of Laplacian Subbands", International Conference on Advances in Pattern Recognition, pp.329-332, 2009.
  12. Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing Third Edition, Prentice- Hall, 2007.
  13. Haralick R.M., "Comparing the laplacian zero crossing edge detector with the second directional derivative edge detector", Proc. IEEE international Conference on Robotics and Automation, vol.2, pp.452-457, 1985.
  14. Yong-Hoon Lee, Park S.Y., "A study of convex/concave edges and edge-enhancing operators based on the Laplacian", IEEE Trans. on Circuits and Systems, vol.37, no.7, pp.940-946, 1990. https://doi.org/10.1109/31.55069
  15. Amarunnishad, T.M., Govindan, V.K., Mathew, A.T., "A Fuzzy Complement Edge Operator", International Conference on Advanced Computing and Communications, pp. 344-348, 2006.
  16. Khunteta, A., Ghosh, D., "Edge detection via fuzzy rule-based edge strength estimation and optimal threshold selection using PSO," International Conference on Industrial and Information Systems, pp.560-565, 2013.
  17. Wang Can, Su Weimin, Gu Hong, Shao Hua, "Edge detection of SAR images using incorporate shift-invariant DWT and binarization method," International Conference on Signal Processing, vol.1,pp.745-748,2012.
  18. Guoqing Xu, Xiaocui Wu, Li Liu, Zhengbin Wu, "Real-time pedestrian detection based on edge factor and Histogram of Oriented Gradient," IEEE International Conference on Information and Automation, pp.384-389, 2011.
  19. Yan Wan, Shanshan Jia, Dong Wang, "Edge Detection Algorithm Based on Grey System Theory Combined with Directed Graph," International Conference on, pp.180-185, 2013.
  20. Ohsaki, M., Sugiyama, T., Ohno, H., "Evaluation of edge detection methods through psychological tests-is the detected edge really desirable for humans?," International Conference on Systems, Man, and Cybernetics, vol.1, pp.671-677, 2000.