Aerial infrared target recognition based on lightweight convolutional neural network

Tingting Cui; Linbo Tang; Yong Heng; Zhenzhen Li; Jinghong Nan

doi:10.1117/12.2539612

14 August 2019 Aerial infrared target recognition based on lightweight convolutional neural network

Tingting Cui, Linbo Tang, Yong Heng, Zhenzhen Li, Jinghong Nan

Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111791B (2019) https://doi.org/10.1117/12.2539612
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China

Abstract

Robust aerial infrared target recognition with multi-scale and multi-angle characteristics is a key technique in infrared systems. However, traditional algorithms often fail to achieve a high accuracy and robustness due to simple features and classifiers. Moreover, deep learning algorithms mainly focus on improving accuracy with the price of high complexity. To address above issues, we propose a two-stage lightweight aerial infrared target recognition based on convolutional neural networks(CNN). We propose the coarse region extraction based on the local contrast in the first stage, which combines infrared image characteristics properly. In the second stage, we propose the find target recognition, which constructs lightweight CNN by changing network layers and convolution kernels. Experimental results demonstrate the algorithm proposed can achieve recognition for six kinds of aerial infrared target. Compared with other algorithms, our algorithm obtains higher accuracy and robustness.

Citation Download Citation

Tingting Cui, Linbo Tang, Yong Heng, Zhenzhen Li, and Jinghong Nan "Aerial infrared target recognition based on lightweight convolutional neural network", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111791B (14 August 2019); https://doi.org/10.1117/12.2539612

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