Infrared image target detection system based on RV1126

Jiayi Zhu; Yi Zhou; Daozhong Jiang; Hongtao Wang; Rui Han; Tong Yin; Shu Li

doi:10.1117/12.2617410

15 February 2022 Infrared image target detection system based on RV1126

Jiayi Zhu, Yi Zhou, Daozhong Jiang, Hongtao Wang, Rui Han, Tong Yin, Shu Li

Proceedings Volume 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021); 1216650 (2022) https://doi.org/10.1117/12.2617410
Event: Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 2021, Hong Kong, Hong Kong

Abstract

The computing power of the image processor of the handheld viewing system is usually low, which brings some difficulties to the image processing. In this article, an infrared image target detection system is built with the RV1126 development board as the core. Compared with visible light, infrared image has the characteristics of low resolution and blurred details of small targets. According to the above characteristics, conventional image processing algorithms are difficult to deploy to embedded infrared image target detection systems. Therefore, this article uses SSD neural network to train the infrared target detection model, and converts the model into an infrared target detection model that can be deployed on RV1126 development board through Rknn. The actual test shows the SSD target detection network can achieve intelligent target detection and recognition on the RV1126-based embedded platform in the infrared image target detection.

Citation Download Citation

Jiayi Zhu, Yi Zhou, Daozhong Jiang, Hongtao Wang, Rui Han, Tong Yin, and Shu Li "Infrared image target detection system based on RV1126", Proc. SPIE 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 1216650 (15 February 2022); https://doi.org/10.1117/12.2617410

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