Abstract
In this article, we study and propose an adaptive thresholding segmentation method for dermoscopic images with Gabor filters and Principal Component Analysis. The Gabor filters is used for extracting statistical features of image and the Principal Component Analysis is applied for transforming features to various bases. In experiments, we implement tests with the ISIC dataset. Segmentation results are assessed by the Dice and the Jaccard similarities. We also compare the proposed method to other similar methods to prove its own effectiveness.
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Thanh, D.N.H., Hien, N.N., Surya Prasath, V.B., Erkan, U., Khamparia, A. (2020). Adaptive Thresholding Skin Lesion Segmentation with Gabor Filters and Principal Component Analysis. In: Solanki, V., Hoang, M., Lu, Z., Pattnaik, P. (eds) Intelligent Computing in Engineering. Advances in Intelligent Systems and Computing, vol 1125. Springer, Singapore. https://doi.org/10.1007/978-981-15-2780-7_87
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DOI: https://doi.org/10.1007/978-981-15-2780-7_87
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