Classical Algorithm vs. Machine Learning in Objects Recognition
Jakub Czygier , Piotr Tomaszuk , Aneta Łukowska , Paweł Straszyński , Kazimierz Dzierżek
AbstractThis article focuses on two most popular methods of detecting regular shapes in the pictures. Over the past years, image processing and object recognition are entering our lives more and more. The difference between a classical algorithm and machine learning was analyzed, in case of a tennis ball recognition on photos. It has been created on own dataset to avoid a uniform background and bright colors. Images were taken with a low-cost camera in different conditions. Creating the classical algorithm and machine learning and comparing the accuracy, false flags and performance of the two methods are described.
|Publication size in sheets||0.55|
|Book||Kohei Arai, Kapoor Supryia (eds.): Advances in Computer Vision: Proceedings of the 2019 Computer Vision Conference (CVC). Vol. 2, Advances in Intelligent Systems and Computing, vol. 944, 2020, Springer, ISBN 978-3-030-17797-3, [978-3-030-17798-0], 766 p., DOI:10.1007/978-3-030-17798-0|
|Keywords in English||object recognition, machine learning, image processing, classification, neural network|
|Internal identifier||ROC 19-20|
|Score||= 20.0, 17-01-2020, MonographChapterAuthor|
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