Abstract
Image segmentation is considered as a necessary step towards accurate medical analysis by extracting the crucial medical information in identifying abnormalities. This study proposes a new technique for segmentation a malignant melanoma in images. A new filter is proposed for smoothing input images and more accurate segmentation based on fractional Poisson. In the pre-processing step, eight masks of size n × n are created to eliminate noise and obtain a smooth image. The watershed algorithm is used for segmentation with morphological operation to better segment the skin lesion area. The proposed method was capable of improving the accuracy of the segmentation up to 96.47%.
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Acknowledgements
The authors would like to thank both Dr. Joaquim M. da Cunha Viana and Mr. Navid Razmjooy for providing the dermoscopic images used in this study. We would also like to thank skin specialist Dr. Mohammed Ahmed, for providing the necessary information for this study. This research is supported by the Fundamental Research Grant Scheme (FRGS), Project: FP073-2015A from Ministry of Higher Education, Malaysia.
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Al-abayechi, A.A.A., Jalab, H.A., Ibrahim, R.W., Hasan, A.M. (2017). Image Enhancement Based on Fractional Poisson for Segmentation of Skin Lesions Using the Watershed Transform. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2017. Lecture Notes in Computer Science(), vol 10645. Springer, Cham. https://doi.org/10.1007/978-3-319-70010-6_23
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DOI: https://doi.org/10.1007/978-3-319-70010-6_23
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