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  1. Home
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  4. Region of adaptive threshold segmentation between mean, median and otsu threshold for dental age assessment
 
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Region of adaptive threshold segmentation between mean, median and otsu threshold for dental age assessment

Journal
I4CT 2014 - 1st International Conference on Computer, Communications, and Control Technology, Proceedings
Date Issued
2014
Author(s)
Mohamed Razali M.R.
Ahmad N.S.
Mohd Zaki Z.
Ismail W.
DOI
10.1109/I4CT.2014.6914204
Abstract
Adaptive threshold works at pixel level and the result of the adaptive threshold is either background or foreground. The adaptive threshold produces superior result compared to global threshold, especially for the images that have uneven pixel intensity distribution. In the dental age assessment, X-ray image is used as an aid to estimate the age of the person. The existing process of assessment is done manually. However, this can be made automatically. The process of automated dental age assessment, require threshold segmentation to separate the background and the teeth area. In order to optimize the result of the adaptive threshold, it depends on the threshold value. In this paper, we present three methods (i.e. mean, median and OTSU) to estimate the range of the threshold value. The result of the study shown that the median threshold provides better results than the mean and OTSU thresholds. In terms of the region of the segmentation, median threshold value covers more teeth followed by mean threshold and OTSU threshold. The region of segmentation is important because one of the requirements in Demirjian method is to assess all the teeth types in quadrant 2 and quadrant 3.Based on the result of the experiment shown the region of median threshold able to segment most of the teeth area in quadrant 2 and quadrant 3. � 2014 IEEE.
Subjects

Adaptive Threshold

Demirjian

Segmentation

Computers

Image segmentation

Adaptive threshold se...

Adaptive thresholds

Demirjian

Global threshold

Pixel intensities

Threshold segmentatio...

Threshold-value

X-ray image

Pixels

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