Adjusting the brightness and contrast parameters of digital video cameras using artificial neural networks

Serhiy Balovsyak; Khrystyna Odaiska; Oleksandra Yakovenko; Inna Iakovlieva

doi:10.1117/12.3009429

5 January 2024 Adjusting the brightness and contrast parameters of digital video cameras using artificial neural networks

Serhiy Balovsyak, Khrystyna Odaiska, Oleksandra Yakovenko, Inna Iakovlieva

Author Affiliations +

Proceedings Volume 12938, Sixteenth International Conference on Correlation Optics; 129380I (2024) https://doi.org/10.1117/12.3009429
Event: International Conference Correlation Optics (COR 2023), 2023, Chernivtsi, Ukraine

Abstract

A computer system for adjusting the «Brightness» and «Contrast» parameters of USB video cameras is developed, which consists of video cameras, computer and Python software. The settings of the video camera are performed by a computer program using an artificial neural network (ANN). A three-layer perceptron with learning by the method of backpropagation was used as an ANN. The inputs of the ANN are histograms of the brightness of the images, that read from the video camera. The ANN training dataset contained a series of images obtained at different values of the "Brightness" and "Contrast" parameters of the video camera. The settings of the video camera parameters are performed iteratively with a given step. An experimental test of the developed system for adjusting the "Brightness" and "Contrast" parameters of the video camera was performed, as a result of which the visual quality of the video stream was increased.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Serhiy Balovsyak, Khrystyna Odaiska, Oleksandra Yakovenko, and Inna Iakovlieva "Adjusting the brightness and contrast parameters of digital video cameras using artificial neural networks", Proc. SPIE 12938, Sixteenth International Conference on Correlation Optics, 129380I (5 January 2024); https://doi.org/10.1117/12.3009429

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KEYWORDS

Video

Cameras

Artificial neural networks

Education and training

Computing systems

Imaging systems

Digital cameras

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