3D object recognition with photon-counting integral imaging using independent component analysis

Cuong Manh Do

doi:10.1117/12.859429

7 September 2010 3D object recognition with photon-counting integral imaging using independent component analysis

Cuong Manh Do

Author Affiliations +

Proceedings Volume 7799, Mathematics of Data/Image Coding, Compression, and Encryption with Applications XII; 77990A (2010) https://doi.org/10.1117/12.859429
Event: SPIE Optical Engineering + Applications, 2010, San Diego, California, United States

Abstract

The author presents an overview of 3D object recognition with photon-counting integral imaging using Independent Component Analysis (ICA). High resolution elemental images of 3D objects are captured at different angles to allow object recognition at different orientations using synthetic aperture integral imaging (SAII). Generated photon-counting elemental images are used to reconstruct the 3D images at different distances from the camera lens using a maximum a posteriori estimation method. The kurtosis maximization-based algorithm is applied as a non-gaussian maximization method to extract the independent features from the training data set. High dimensional data is pre-processed using Principal Component Analysis (PCA) to reduce the number of dimensions. The author demonstrates how this method can effectively recognize 3D objects despite a small expected number of photons. This may be important for low light applications in medical or other settings.

Citation Download Citation

Cuong Manh Do "3D object recognition with photon-counting integral imaging using independent component analysis", Proc. SPIE 7799, Mathematics of Data/Image Coding, Compression, and Encryption with Applications XII, 77990A (7 September 2010); https://doi.org/10.1117/12.859429

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