上海交通大学学报（英文版） ›› 2013, Vol. 18 ›› Issue (4): 448-453.doi: 10.1007/s12204-013-1414-1

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Modified Gray Level Difference-Based Thresholding Segmentation and its Application in X-Ray Welding Image

TONG Tong* (佟 彤), CAI Yan (孙大为), SUN Da-wei (孙大为), WU Yi-xiong (吴毅雄)   

  1. (Shanghai Key Laboratory of Materials Laser Processing and Modification, Shanghai Jiaotong University, Shanghai 200240, China)
  • 出版日期:2013-08-28 发布日期:2013-08-12
  • 通讯作者: TONG Tong* (佟 彤) E-mail:lunwenpapertt@sina.com

Modified Gray Level Difference-Based Thresholding Segmentation and its Application in X-Ray Welding Image

TONG Tong* (佟 彤), CAI Yan (孙大为), SUN Da-wei (孙大为), WU Yi-xiong (吴毅雄)   

  1. (Shanghai Key Laboratory of Materials Laser Processing and Modification, Shanghai Jiaotong University, Shanghai 200240, China)
  • Online:2013-08-28 Published:2013-08-12
  • Contact: TONG Tong* (佟 彤) E-mail:lunwenpapertt@sina.com

摘要： Thresholding is a popular image segmentation method that often requires as a preliminary and indispensable stage in the computer aided image process, particularly in the analysis of X-ray welding images. In this paper, a modified gray level difference-based transition region extraction and thresholding algorithm is presented for segmentation of the images that have been corrupted by intensity inhomogeneities or noise. Classical gray level difference algorithm is improved by selective output of the result of the maximum or the minimum of the gray level with the pixels in the surrounding, and multi-structuring of neighborhood window is used to represent the essence of transition region. The proposed algorithm could robustly measure the gray level changes, and accurately extract transition region of an image. Comparisons with other approaches demonstrate the superior performance of the proposed algorithm.

关键词: image segmentation, transition region, gray level difference, welding image

Abstract: Thresholding is a popular image segmentation method that often requires as a preliminary and indispensable stage in the computer aided image process, particularly in the analysis of X-ray welding images. In this paper, a modified gray level difference-based transition region extraction and thresholding algorithm is presented for segmentation of the images that have been corrupted by intensity inhomogeneities or noise. Classical gray level difference algorithm is improved by selective output of the result of the maximum or the minimum of the gray level with the pixels in the surrounding, and multi-structuring of neighborhood window is used to represent the essence of transition region. The proposed algorithm could robustly measure the gray level changes, and accurately extract transition region of an image. Comparisons with other approaches demonstrate the superior performance of the proposed algorithm.

Key words: image segmentation, transition region, gray level difference, welding image

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