High-speed image-free target detection and classification in single-pixel imaging

Saad Rizvi; Jie Cao; Qun Hao

doi:10.1117/12.2580557

8 November 2020 High-speed image-free target detection and classification in single-pixel imaging

Saad Rizvi, Jie Cao, Qun Hao

Proceedings Volume 11525, SPIE Future Sensing Technologies; 115250X (2020) https://doi.org/10.1117/12.2580557
Event: SPIE Future Sensing Technologies, 2020, Online Only

Abstract

In this paper, an efficient image-free target detection and classification framework for single-pixel imaging (SPI) is presented. The proposed method captures target information by sampling it with very few patterns (at 1-10% sampling rate), and employs signal-processing based feature extraction coupled with radial basis function neural network (RBF-NN) for accurate target classification. The proposed method can replace existing deep learning (DL) based target detection and classification methods because of its high-speed, accuracy and simple shallow design.

Conference Presentation

Citation Download Citation

Saad Rizvi, Jie Cao, and Qun Hao "High-speed image-free target detection and classification in single-pixel imaging", Proc. SPIE 11525, SPIE Future Sensing Technologies, 115250X (8 November 2020); https://doi.org/10.1117/12.2580557

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