An extrinsic Fabry-Perot interferometric (EFPI) optical fiber hydrogen sensor based on palladium silver (Pd-Ag) film is
designed for hydrogen leakage detection. The sensing mechanism of such a sensor is based on the mechanical stress that
is induced in the Pd-Ag film when it absorbs hydrogen. The sensor system which is portable and suitable for field
detection is formed by a conventional coupler, a low-power LED operating at 850 nm, and a high resolution miniature
spectrometer. To obtain the absolute length of the EFPI air gap, a cross-correlation signal processing method is
introduced.The sensor is suitable for monitoring concentrations of hydrogen below the lower explosive limit.
Optical coherence tomography (OCT) is a recent imaging method that allows high-resolution, cross-sectional imaging through tissues and materials. Over the past 18 years, OCT has been successfully used in disease diagnosis, biomedical research, material evaluation, and many other domains. As OCT is a recent imaging method, until now surgeons have limited experience using it. In addition, the number of images obtained from the imaging device is too large, so we need an automated method to analyze them. We propose a novel method for automated classification of OCT images based on local features and earth mover's distance (EMD). We evaluated our algorithm using an OCT image set which contains two kinds of skin images, normal skin and nevus flammeus. Experimental results demonstrate the effectiveness of our method, which achieved classification accuracy of 0.97 for an EMD+KNN scheme and 0.99 for an EMD+SVM (support vector machine) scheme, much higher than the previous method. Our approach is especially suitable for nonhomogeneous images and could be applied to a wide range of OCT images.
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