A local real-time bar detector based on the multiscale Radon transform

Ricardo Oliva-García; Óscar Gómez-Cárdenes; José G. Marichal-Hernández; Javier Martín-Hernández; Jonas Phillip-Lüke; José M. Rodríguez-Ramos

doi:10.1117/12.2617411

27 May 2022 A local real-time bar detector based on the multiscale Radon transform

Ricardo Oliva-García, Óscar Gómez-Cárdenes, José G. Marichal-Hernández, Javier Martín-Hernández, Jonas Phillip-Lüke, José M. Rodríguez-Ramos

Author Affiliations +

Proceedings Volume 12102, Real-Time Image Processing and Deep Learning 2022; 121020A (2022) https://doi.org/10.1117/12.2617411
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

We propose a local bar-shaped structure detector that works in real time on high-resolution images. It is based on the Radon transform. Specifically in the muti-scale variant, which is especially fast because it works in integer mathematics and does not use interpolation. The Radon transform conventionally works on the whole image, and not locally. In this paper we describe how by stopping at the early stages of the Radon transform we are able to locate structures locally. We also provide an evaluation of the performance of the algorithm running on the CPU, GPU and DSP of mobile devices to process at acquisition time the images coming from the device's camera.

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Ricardo Oliva-García, Óscar Gómez-Cárdenes, José G. Marichal-Hernández, Javier Martín-Hernández, Jonas Phillip-Lüke, and José M. Rodríguez-Ramos "A local real-time bar detector based on the multiscale Radon transform", Proc. SPIE 12102, Real-Time Image Processing and Deep Learning 2022, 121020A (27 May 2022); https://doi.org/10.1117/12.2617411

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