Abstract
We demonstrate that a single 6mm line sample of simulated near-field speckle intensity suffices for accurate estimation of the concentration of dielectric micro-particles over a range from 104 to 6⋅106 particles per ml. For this estimation, we analyze the speckle using both standard methods (linear principal component analysis, support vector machine (SVM)) and a neural network, in the form of a sparse stacked autoencoder (SSAE) with a softmax classifier or with an SVM. Using an SSAE with SVM, we classify line speckle samples according to particle concentration with an average accuracy of over 78%, with other methods close behind.
Highlights
Transmission of coherent light through a large collection of randomly distributed small particles typically results in the formation of a speckle pattern, see Fig. 1
We demonstrate that a single 6mm line sample of simulated near-field speckle intensity suffices for accurate estimation of the concentration of dielectric micro-particles over a range from 104 to 6 · 106 particles per ml
Using an sparse stacked autoencoder (SSAE) with support vector machine (SVM), we classify line speckle samples according to particle concentration with an average accuracy of over 78%, with other methods close behind
Summary
Transmission of coherent light through a large collection of randomly distributed small particles typically results in the formation of a speckle pattern, see Fig. 1. It is conceivable that the industrial material identification or characterization by speckle analysis [16,17,18] would favor fast image acquisition and processing, provided the reconstruction quality is comparable with the 2D case. Applications such as wearable sensors for non-invasive glucose concentration measurement [19] could benefit from simplifying the detector, decreasing the memory usage, the required processing capability and the power consumption. Briefly explains how we compute the near-field speckle throughout this paper, and how a standard statistical analysis of line speckle would perform in the context of particle concentration estimation.
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