Open AccessSensitive test for sea mine identification based on polarization-aided image processing
Author(s) -
Isabelle Léonard,
Ayman Alfalou,
Christian Brosseau
Publication year - 2013
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.21.029283
Subject(s) - computer science , preprocessor , underwater , artificial intelligence , constant false alarm rate , computer vision , polarizing filter , filter (signal processing) , image processing , visibility , image quality , false alarm , pattern recognition (psychology) , remote sensing , optical filter , optics , image (mathematics) , geology , oceanography , physics
Techniques are widely sought to detect and identify sea mines. This issue is characterized by complicated mine shapes and underwater light propagation dependencies. In a preliminary study we use a preprocessing step for denoising underwater images before applying the algorithm for mine detection. Once a mine is detected, the protocol for identifying it is activated. Among many correlation filters, we have focused our attention on the asymmetric segmented phase-only filter for quantifying the recognition rate because it allows us to significantly increase the number of reference images in the fabrication of this filter. Yet they are not entirely satisfactory in terms of recognition rate and the obtained images revealed to be of low quality. In this report, we propose a way to improve upon this preliminary study by using a single wavelength polarimetric camera in order to denoise the images. This permits us to enhance images and improve depth visibility. We present illustrative results using in situ polarization imaging of a target through a milk-water mixture and demonstrate that our challenging objective of increasing the detection rate and decreasing the false alarm rate has been achieved.