Brian W.-H. Ng

T-Ray Sensing and Imaging

T-ray wavelengths are long enough to pass through dry, nonpolar objects opaque at visible wavelengths, but short enough to be manipulated by optical components to form an image. Sensing in this band potentially provides advantages in a number of areas of interest to security and defense such as screening of personnel for hidden objects and the retection of chemical and biological agents. Several private companies are developing smaller, reliable cheaper systems allowing for commercialization and this motivates us to review a number of promising applications within this paper. While there are a number of challenges to be overcome there is little doubt that T-ray technology will play a significant role in the near future for advancement of security, public health, and defense.

Support Vector Machine Applications in Terahertz Pulsed Signals Feature Sets

In the past decade, terahertz radiation (T-rays) have been extensively applied within the fields of industrial and biomedical imaging, owing to their noninvasive property. Support vector machine (SVM) learning algorithms are sufficiently powerful to detect patterns hidden inside noisy biomedical measurements. This paper introduces a frequency orientation component method to extract T-ray feature sets for the application of two- and multiclass classification using SVMs. Effective discriminations of ribonucleic acid (RNA) samples and various powdered substances are demonstrated. The development of this method has become important in T-ray chemical sensing and image processing, which results in enhanced detectability useful for many applications, such as quality control, security detection and clinic diagnosis.

Wavelet based local tomographic image using terahertz techniques

Terahertz computed tomography has been developed based on coherent THz detection and filtered back projection (FBP) algorithms, which allows the global imaging of the internal structure and extraction of the frequency dependent properties. It offers a promising approach for achieving non-invasive inspection of solid materials. However, with traditional CT techniques, i.e. FBP algorithms, full exposure data are needed for inverting the Radon transform to produce cross sectional images. This remains true even if the region of interest is a small subset of the entire image. For time-domain terahertz measurements, the requirement for full exposure data is impractical due to the slow measurement process. This paper explores time domain reconstruction of terahertz measurements by applying wavelet-based filtered back projection algorithms for recovery of a local area of interest from terahertz measurements within its vicinity, and thus improves the feasibility of using terahertz imaging to detect defects in solid materials and diagnose disease states for clinical practise, to name a few applications.

2-D Wavelet Segmentation in 3-D T-Ray Tomography

In this letter, segmentation techniques for terahertz (T-ray) computed tomographic (CT) imaging are investigated. A set of linear image fusion and novel wavelet scale correlation segmentation techniques is adopted to achieve material discrimination within a 3-D object. The methods are applied to a T-ray CT image dataset taken from a plastic vial containing a plastic tube. This setup simulates the imaging of a simple nested organic structure, which provides an indication of the potential for using T-ray CT imaging to achieve T-ray pulsed signal classification of heterogeneous layers

Automated Authorship Attribution Using Advanced Signal Classification Techniques

In this paper, we develop two automated authorship attribution schemes, one based on Multiple Discriminant Analysis (MDA) and the other based on a Support Vector Machine (SVM). The classification features we exploit are based on word frequencies in the text. We adopt an approach of preprocessing each text by stripping it of all characters except a-z and space. This is in order to increase the portability of the software to different types of texts. We test the methodology on a corpus of undisputed English texts, and use leave-one-out cross validation to demonstrate classification accuracies in excess of 90%. We further test our methods on the Federalist Papers, which have a partly disputed authorship and a fair degree of scholarly consensus. And finally, we apply our methodology to the question of the authorship of the Letter to the Hebrews by comparing it against a number of original Greek texts of known authorship. These tests identify where some of the limitations lie, motivating a number of open questions for future work. An open source implementation of our methodology is freely available for use at https://github.com/matthewberryman/author-detection.

Terahertz scattering by granular composite materials: An effective medium theory

Terahertz (THz) spectroscopy and imaging have emerged as important tools for identification and classification of various substances, which exhibit absorption characteristics at distinct frequencies in the THz range. The spectral fingerprints can potentially be distorted or obscured by electromagnetic scattering caused by the granular nature of some substances. In this paper, we present THz time domain transmission measurements of granular polyethylene powders in order to investigate an effective medium theory that yields a parameterized model, which can be used to estimate the empirical measurements to good accuracy.

Low-cost ultra-thin broadband terahertz beam-splitter

A low-cost terahertz beam-splitter is fabricated using ultra-thin LDPE plastic sheeting coated with a conducting silver layer. The beam splitting ratio is determined as a function of the thickness of the silver layer--thus any required splitting ratio can be printed on demand with a suitable rapid prototyping technology. The low-cost aspect is a consequence of the fact that ultra-thin LDPE sheeting is readily obtainable, known more commonly as domestic plastic wrap or cling wrap. The proposed beam-splitter has numerous advantages over float zone silicon wafers commonly used within the terahertz frequency range. These advantages include low-cost, ease of handling, ultra-thin thickness, and any required beam splitting ratio can be readily fabricated. Furthermore, as the beam-splitter is ultra-thin, it presents low loss and does not suffer from Fabry-Pérot effects. Measurements performed on manufactured prototypes with different splitting ratios demonstrate a good agreement with our theoretical model in both P and S polarizations, exhibiting nearly frequency-independent splitting ratios in the terahertz frequency range.

Reduction of Scattering Effects in THz-TDS Signals

The scattering of terahertz radiation from the granular nature of a sample can potentially distort or obscure its characteristic spectral features. Several techniques have been proposed to reduce the effects of scattering in terahertz time-domain spectroscopy (THz-TDS) measurements, that usually require a complex measurement apparatus or rely on specific information about the sample under study. However, in real-world applications a priori information of the sample is not always known and therefore the applicability of these techniques may be limited. In this letter, we present a method for estimating and mitigating scattering effects in THz-TDS measurements for samples made of material exhibiting sharp and sparse absorption features, without requiring information of its granularity, refractive index, and density.

Estimating adders for a low density parity check decoder

Low density parity check decoders use computation nodes with multioperand adders on their critical path. This paper describes the design of estimating multioperand adders to reduce the latency, power and area of these nodes. The new estimating adders occasionally produce inaccurate results. The effect of these errors and the subsequent trade-off between latency and decoder frame error rate is examined. For the decoder investigated it is found that the estimating adders do not degrade the frame error rate.

Local Computed Tomography Using a THz Quantum Cascade Laser

This paper investigates local reconstruction techniques for extracting region-of-interest (ROI) from a 3-D terahertz imaging setup using a quantum cascade laser (QCL). The advantage of local reconstruction is the reduction in the required measurement time. Difficulties with limited projection angles and image noise make the development of accurate reconstruction algorithms particularly challenging. In this paper, both wavelet-based and traditional filtered back projection (FBP) techniques are investigated. Segmentation algorithms are applied to reconstructed images with low contrast and the resultant segments are compared with a known ground truth to explore the ability of a QCL to image target objects with complex contours. In our experiments, a polystyrene object with a hole drilled inside is used as the imaging target. The region of interest is adjusted through changing the size of the exposure regions. It is found that 3-D local reconstruction of the interior hole suffers from shape distortion, since scattering caused by the targets exterior contours introduces errors in the measured optical parameters of the object. It is found that wavelet-based local computed tomography for terahertz image reconstruction results in lower misclassification of pixels than traditional FBP algorithms.