Closed-loop active object recognition with constrained illumination power
Jacques Noom (TU Delft - Mechanical Engineering)
Oleg Soloviev (TU Delft - Mechanical Engineering, Flexible Optical B.V.)
Carlas Smith (TU Delft - ImPhys/Computational Imaging, TU Delft - Mechanical Engineering)
Michel Verhaegen (TU Delft - Mechanical Engineering)
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Abstract
Some applications require high level of image-based classification certainty while keeping the total illumination energy as low as possible. Examples are minimally invasive visual inspection in Industry 4.0, and medical imaging systems such as computed tomography, in which the radiation dose should be kept “as low as is reasonably achievable”. We introduce a sequential object recognition scheme aimed at minimizing phototoxicity or bleaching while achieving a predefined level of decision accuracy. The novel online procedure relies on approximate weighted Bhattacharyya coefficients for determination of future inputs. Simulation results on the MNIST handwritten digit database show how the total illumination energy is decreased with respect to a detection scheme using constant illumination.