Razali M.R.M.Ismail W.Ahmad N.S.Bahari M.Zaki Z.M.Radman A.2024-05-282024-05-282017Mohamed 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/1583218018432-s2.0-85040023409https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040023409&partnerID=40&md5=8e3bab67ae35033bb2fa42f7df84b35ahttps://jtec.utem.edu.my/jtec/article/view/1583https://oarep.usim.edu.my/handle/123456789/8493Thresholding 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.en-USAge estimationImage segmentationImage thresholdingArticle1594