Lensless inference camera: incoherent object recognition through a thin mask with LBP map generation

We propose a preliminary lensless inference camera (LLI camera) specialized for object recognition. The LLI camera performs computationally efficient data preprocessing on the optically encoded pattern through the mask, rather than performing computationally expensive image reconstruction before inference. Therefore, the LLI camera avoids expensive computation and achieves real-time inference. This work proposes a new data preprocessing approach, named local binary patterns map generation, dedicated for optically encoded pattern through the mask. This preprocessing approach greatly improves encoded pattern's robustness to local disturbances in the scene, making the LLI camera's practical application possible. The performance of the LLI camera is analyzed through optical experiments on handwritten digit recognition and gender estimation under conditions with changing illumination and a moving target. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Automated summary

A preliminary lensless inference camera specialized for object recognition, the LLI camera, performs computationally efficient data preprocessing through a new approach called local binary patterns map generation, enhancing robustness to local disturbances and enabling real-time inference.