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Shape From Shading: A Non-iterative Method Using Neural Networks

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1375))

Abstract

Shape from shading is an important domain of computer vision and one of the approaches of 3D reconstruction. In this paper we propose a new method to reconstruct the surface of an object using neural networks. This approach ignores the details of the image for a big gain in noise resistance. It is based on the available boundary information of the surface of the shape to be reconstructed. We will use a neural network to evaluate the variation of the surface for a pixel based on the adjacent pixels. The small number of neurons ensures the speed of the algorithm. The approach is tested on synthetic and real images .

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Correspondence to Lyes Abada .

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Bourahla, O.E.F., Debbah, A.M., Abada, L., Aouat, S. (2021). Shape From Shading: A Non-iterative Method Using Neural Networks. In: Abraham, A., Hanne, T., Castillo, O., Gandhi, N., Nogueira Rios, T., Hong, TP. (eds) Hybrid Intelligent Systems. HIS 2020. Advances in Intelligent Systems and Computing, vol 1375. Springer, Cham. https://doi.org/10.1007/978-3-030-73050-5_74

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