Image warping in dermatological image hair removal Alexandra Nasonova 1 , Andrey Nasonov 1 , Andrey Krylov 1 , Ivan Pechenko 1 , Alexey Umnov 1 , Natalia Makhneva 2 1 Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University 2 Moscow Scientific and Practical Center of Dermatology and Venereology and Cosmetology of Moscow Healthcare Department kryl@cs.msu.ru Abstract. The paper focuses on solving the problem of hair removal in dermatology applications. The proposed hair removal algorithm is based on Gabor filtering and PDE-based image reconstruction. It also includes the edge sharpening stage using a new warping algorithm. The idea of warping is to move pixels from the neighborhood of the blurred edge closer to the edge. The proposed technique preserves the overall luminosity and textures of the image, while making the edges sharper and less noisy. Keywords: Image warping, edge sharpening, hair detection, inpainting, dermatology 1 Introduction One of the main problems of image processing in dermatology applications is the presence of hair which should be removed before image analysis. The survey of state of the art hair removal methods for dermoscopy images is presented in [2]. All existing hair removal algorithms consist of two main stages: detection of pixels covered by hair and restoration of pixels in hair regions with minimal distortion. Hair-removal methods can be broadly classified as linear interpolation techniques, inpainting by non-linear-PDE based diffusion algorithms and exam- ple based methods. An example of linear interpolation hair removal algorithm can be found in [18, 21, 23, 24]. There are works which utilized the concept of non-linear PDE based diffusion [5, 9, 13, 26]. Also, an attention has been paid to remove hair by example based inpainting technique [1, 3, 14, 25]. The paper introduces a new method for the problem of hair removal which adds the edge sharpening as the third main stage additional to hair pixel de- tection and restoration stages. The hair pixel detection stage of the proposed method is based on the algorithm [4] and improves it using Gabor filters for line detection instead of difference of Gaussians. For the pixel restoration stage we use PDE-based algorithm [10].