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Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2012 Vol.2(3): 292-297 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2012.V2.133

An Analysis of Image Enhancement Techniques for Dental X-ray Image Interpretation

Siti Arpah Ahmad, Mohd Nasir Taib, Noor Elaiza Abdul Khalid, and Haslina Taib

Abstract—This paper presents qualitative and quantitative comparison between original images and four image enhancement techniques namely adaptive histogram equalization (AHE), contrast adaptive histogram equalization (CLAHE), median adaptive histogram equalization (MAHE) and sharp contrast adaptive histogram equalization (SCLAHE) applied to dental x-ray images. Dental x-ray images usually taken with low radiation dosage are often presented as dark, low in contrast and noisy. These problems are usually solved with image enhancement techniques. However, choosing an appropriate technique is not an easy task especially for the purpose of disease diagnosis of periapical related lesion. This research involves the collection of ten intra-oral dental x-ray images which were collected from the Faculty of Dentistry UiTM Shah Alam, Malaysia. Each of the enhancement methods is applied to every collected image. A dentist was then asked to do the evaluation using questionnaire. She graded the quality of the images and the diagnostic ability of the periapical pathology observed in the images. Subsequently the quantitative analysis using contrast improvement index (CII), signal to noise ratio (SNR) and root mean square error (RMSE) were done to investigate the characteristic of the images base on the dentist evaluation. The finding shows that the enhancement techniques managed to enhance the pathology slightly better than the original image.

Index Terms—Contrast enhancement, adaptive histogram equalization (AHE), dental X-ray.

Siti Arpah Ahmad and Mohd Nasir Taib are with Faculty of Electrical Engineering, Universiti Teknologi MARA, Shah Alam, 40450, Malaysia (e-mail: arpah@ tmsk.uitm.edu.my; dr.nasir@ ieee.org).
Nor Elaiza Abdul Khalid with Faculty of Computer and Mathematical Science, Universiti Teknologi MARA, Shah Alam, 40450, Malaysia (e-mail: elaiza@tmsk.uitm.edu.my).
HaslinaTaib is with School of Dental Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian Kelantan, Malaysia (e-mail: haslina@kck.usm.my).

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Cite: Siti Arpah Ahmad, Mohd Nasir Taib, Noor Elaiza Abdul Khalid, and Haslina Taib, "An Analysis of Image Enhancement Techniques for Dental X-ray Image Interpretation," International Journal of Machine Learning and Computing vol. 2, no. 3, pp. 292-297, 2012.

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