An Adaptive Thresholding Method for Segmenting Dental X-Ray Images

Authors

  • Muhamad Rizal Mohamed Razali Penang Skills Development Centre, Pulau Pinang, Malaysia. Faculty of Science and Technology, Universiti Sains Islam Malaysia, Negeri Sembilan, Malaysia.
  • Waidah Ismail Faculty of Science and Technology, Universiti Sains Islam Malaysia, Negeri Sembilan, Malaysia.
  • Nazatul Sabariah Ahmad Faculty of Dentistry, Universiti Sains Islam Malaysia, Negeri Sembilan, Malaysia.
  • Mahadi Bahari Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia.
  • Zulkifly Mohd Zaki Faculty of Science and Technology, Universiti Sains Islam Malaysia, Negeri Sembilan, Malaysia.
  • Abduljalil Radman Faculty of Science and Technology, Universiti Sains Islam Malaysia, Negeri Sembilan, Malaysia.

Keywords:

Age Estimation, Image Segmentation, Image Thresholding,

Abstract

Thresholding is a way of segmenting an image into foreground and background according to a fixed constant value called a threshold. Image segmentation based on a constant threshold leads to unsatisfactory results with dental X-ray images due to the uneven distribution of pixel intensity. In this paper, an adaptive thresholding method is proposed to attain promising segmentation results for dental X-ray images. The Mean, Median, Midgrey, Niblack, and OTSU thresholding methods are utilized to delineate the acceptable range of threshold values to be applied for segmenting X-ray images. Experimental results showed that the Median method provides consistency in achieving the best range of threshold values which is between 57 and 86 in greyscale.

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Published

2017-12-30

How to Cite

Mohamed Razali, M. R., Ismail, W., Ahmad, N. S., Bahari, M., Mohd Zaki, Z., & Radman, A. (2017). An Adaptive Thresholding Method for Segmenting Dental X-Ray Images. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(4), 1–5. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1583

Issue

Vol. 9 No. 4: October - December 2017

Section

Articles

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