Closed-loop active object recognition with constrained illumination power

Conference paper (2022)

Authors

J. Noom Team Michel Verhaegen - Mechanical, Maritime and Materials Engineering
O.A. Soloviev Flexible Optical B.V., Team Michel Verhaegen - Mechanical, Maritime and Materials Engineering
C.S. Smith ImPhys/Computational Imaging - AS , Team Carlas Smith - Mechanical, Maritime and Materials Engineering
M.H.G. Verhaegen Team Michel Verhaegen - Mechanical, Maritime and Materials Engineering
Research Group
Team Michel Verhaegen (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 J. Noom, O.A. Soloviev, C.S. Smith, M.H.G. Verhaegen
DOI: https://doi.org/10.1117/12.2618750
More Info
expand_more

Published Date

2022

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Michel Verhaegen

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.

Files

1210203.pdf
(pdf | 0.722 Mb)
Unknown license