ScholarWorks@숙명여자대학교

초록

Various lighting changes are one of the factors that degrade the recognition performance of face images, in particular, when a shadow is formed on a face image due to lighting or surrounding environment, it is a general tendency that recognition performance is greatly degraded. Therefore, if the face image in which the shadow has occurred can be restored to its original state, improvement in face recognition performance can be expected. In this study, we propose a method of mitigating and removing shadows using Pix2pix, one of the representative models of GAN, a hostile generating neural network. Since the Pix2pix GAN model requires a pair of images corresponding to training, for this, we propose an idea to create a virtual training image corresponding to it from a normal face image using various image blending methods and use it as a training pair. Results of testing the model trained using the data generated by the proposed method, it can be seen that the shadows of the face image are naturally reduced and that the facial recognition performance is improved.

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