Modelling and Data Analysis
2024. Vol. 14, no. 1, 41–51
doi:10.17759/mda.2024140103
ISSN: 2219-3758 / 2311-9454 (online)
Application of Convolutional Neural Networks in the Problem of Removing Shadows from Photographs
Abstract
The article proposes a method for removing shadows from photographs using deep learning methods. The proposed method consists of several stages: dividing the image into rectangular fragments of 32x32 pixels, localizing shadows on each fragment, restoring the color of shadowed objects, and combining the fragments back into a whole image. Shadow localization is considered as a semantic segmentation problem; to solve it, a neural network of encoder-decoder architecture has been developed and trained. To restore the color of objects in identified shaded areas, another neural network based on the CDNet architecture is used. Examples of image processing using the developed method are given, including images from a drone, and the high quality of restoration of shaded areas is demonstrated.
General Information
Keywords: computer vision, deep learning, image processing, convolutional neural networks, shadow localization, semantic segmentation
Journal rubric: Data Analysis
Article type: scientific article
DOI: https://doi.org/10.17759/mda.2024140103
Received: 27.02.2024
Accepted:
For citation: Alekseychuk A.S., Mukin Yu.D. Application of Convolutional Neural Networks in the Problem of Removing Shadows from Photographs. Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2024. Vol. 14, no. 1, pp. 41–51. DOI: 10.17759/mda.2024140103. (In Russ., аbstr. in Engl.)
References
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