Paul O'Leary

Bio: Paul O'Leary is an academic researcher from University of Leoben. The author has contributed to research in topics: Calibration & Oversampling. The author has an hindex of 26, co-authored 161 publications receiving 2902 citations. Previous affiliations of Paul O'Leary include Nominum & Joanneum Research.

Analogue Realizations of Fractional-Order Controllers

Abstract: An approach to the design of analogue circuits, implementingfractional-order controllers, is presented. The suggestedapproach is based on the use of continued fraction expansions;in the case of negative coefficients in a continued fractionexpansion, the use of negative impedance converters is proposed.Several possible methods for obtaining suitable rational appromixationsand continued fraction expansions are discussed. An exampleof realization of a fractional-order Iλ controlleris presented and illustrated by obtained measurements.The suggested approach can be used for the control of veryfast processes, where the use of digital controllers isdifficult or impossible.

Phosphorescent Complexes of Porphyrin Ketones: Optical Properties and Application to Oxygen Sensing

Abstract: A new class of dyes, platinum(II) and palladium(II) complexes of the porphyrin ketones (or oxochlorins), exhibiting strong phosphorescence at room temperature is described. Several representative compounds were prepared and studied by spectral luminescence methods in solution. Compared to the related porphyrin and chlorin complexes, the new dyes display high photochemical stability, long wave spectral characteristics, and good compatibility with semiconductor optoelectronics (e.g., excitation by light-emitting diodes). These properties make the new dyes promising for a number of relevant applications, such as quenched phosphorescence sensing and phosphorescence probing (e.g., in binding assays). Analytical application of the porphyrin ketone complexes to phosphorescence lifetime-based sensing of molecular oxygen is described. Platinum(II) octaethylporphine ketone was dissolved in a polystyrene layer to give an oxygen-sensitive film. Oxygen measurements were performed with a prototype fiber-optic instrument based on solid-state components, such as light-emitting diodes and photodiodes. The instrument measured phosphorescence lifetime via changes in phase shift. The phosphorescence lifetime was determined to change from about 61.4 μs at zero oxygen to 16.3 μs in air (210 hPa of oxygen) at 22 °C. The analytically useful range of the sensor was 0-210 hPa of oxygen partial pressure, with a detection limit of 1.5 hPa. The precision of the device was 1.0 hPa at 210 hPa of oxygen and 0.5 hPa at zero oxygen.

Image Acquisition Techniques for Automatic Visual Inspection of Metallic Surfaces

Abstract: This paper provides an overview of three different image acquisition approaches for automatic visual inspection of metallic surfaces. The first method is concerned with gray-level intensity imaging, whereby the most commonly employed lighting techniques are surveyed. Subsequently, two range imaging techniques are introduced which may succeed in contrast to intensity imaging if the reflection property across the intact surface changes. However, range imaging for surface inspection is restricted to surface defects with three-dimensional characteristics, e.g. cavities. One range imaging approach is based on light sectioning in conjunction with fast imaging sensors. The second introduced range imaging technique is photometric stereo.

Least squares surface reconstruction from measured gradient fields

Abstract: This paper presents a new method for the reconstruction of a surface from its x and y gradient field, measured, for example, via Photometric Stereo. The new algorithm produces the unique discrete surface whose gradients are equal to the measured gradients in the global vertical-distance least-squares sense. We show that it has been erroneously believed that this problem has been solved before via the solution of a Poisson equation. The numerical behaviour of the algorithm allows for reliable surface reconstruction on exceedingly large scales, e.g., full digital images; moreover, the algorithm is direct, i.e., non-iterative. We demonstrate the algorithm with synthetic data as well as real data obtained via photometric stereo. The algorithm does not exhibit a low-frequency bias and is not unrealistically constrained to arbitrary boundary conditions as in previous solutions. In fact, it is the first algorithm which can reconstruct a surface of polynomial degree two or higher exactly. It is hence the first viable algorithm for online industrial inspection where real defects (as opposed to phantom defects) must be identified in a robust manner.

Computer Vision: Algorithms and Applications

Abstract: Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art? Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of recipes, this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Regularization Of Inverse Problems

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