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A Novel Method of Pre-processing Using Dental X-Ray Images by Adaptive Morpho Histo Wavelet Denoising (AMHW) Method

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Information and Communication Technology for Development for Africa (ICT4DA 2019)

Abstract

Dental X-ray imaging is one of the medical imaging techniques used by the dental practitioners. This method uses dental X-ray diagnostic file. This has been found to be very helpful to dental doctors to get more information on the oral disease in patients. X-ray radiation is used for wide range of medical imaging applications. Once the technique becomes a success, it produces good quality X-ray images. The X-ray image is very essential for the treatment planning and procedure for the patients. The X-ray image has lot of artifacts which can be removed through various preprocessing methods. In this paper a novel method for preprocessing is introduced through the fusion of adaptive histogram, morphological enhancement and wavelet de-noising (AWHM). The input X-ray image is initially checked with various other existing preprocessing methods such as adaptive histogram equalization, un sharp masking, Gaussian low pass and high pass methods, high pass adaptation, morphological enhancement, contrast enhancement and wavelet de-noising. AWHM is giving better result than all the other methods. The existing method and novel method is compared with various non-reference parameters and the reference parameter. The result of the novel method is better than all other existing methods. The Contrast Per Pixel technique is used for analyzing the pixel brightness in a more better way. Since the CPP value is higher in AMHW method it indicates AMHW method is the best among the pre-existing methods.

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Correspondence to S. G. Saju Simon .

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Simon, S.G.S., Joseph, X.F., Waktola, A.T., Senay, D. (2019). A Novel Method of Pre-processing Using Dental X-Ray Images by Adaptive Morpho Histo Wavelet Denoising (AMHW) Method. In: Mekuria, F., Nigussie, E., Tegegne, T. (eds) Information and Communication Technology for Development for Africa. ICT4DA 2019. Communications in Computer and Information Science, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-26630-1_1

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  • DOI: https://doi.org/10.1007/978-3-030-26630-1_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26629-5

  • Online ISBN: 978-3-030-26630-1

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