Optical Review

, Volume 24, Issue 2, pp 117–120

Object recognition through a multi-mode fiber

Regular Paper

DOI: 10.1007/s10043-017-0303-5

Cite this article as:
Takagi, R., Horisaki, R. & Tanida, J. Opt Rev (2017) 24: 117. doi:10.1007/s10043-017-0303-5

Abstract

We present a method of recognizing an object through a multi-mode fiber. A number of speckle patterns transmitted through a multi-mode fiber are provided to a classifier based on machine learning. We experimentally demonstrated binary classification of face and non-face targets based on the method. The measurement process of the experimental setup was random and nonlinear because a multi-mode fiber is a typical strongly scattering medium and any reference light was not used in our setup. Comparisons between three supervised learning methods, support vector machine, adaptive boosting, and neural network, are also provided. All of those learning methods achieved high accuracy rates at about 90% for the classification. The approach presented here can realize a compact and smart optical sensor. It is practically useful for medical applications, such as endoscopy. Also our study indicated a promising utilization of artificial intelligence, which has rapidly progressed, for reducing optical and computational costs in optical sensing systems.

Keywords

Object recognition and classification Machine learning Multi-mode fiber Support vector machine Adaptive boosting Neural network 

Copyright information

© The Optical Society of Japan 2017

Authors and Affiliations

  1. 1.Department of Information and Physical Sciences, Graduate School of Information Science and TechnologyOsaka UniversityOsakaJapan

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