Mitigating the effects of atmospheric distortion using DT-CWT fusion

This paper describes a new method for mitigating the effects of atmospheric distortion on observed images, particularly airborne turbulence which degrades a region of interest (ROI). In order to provide accurate detail from objects behind the dis-torting layer, a simple and efficient frame selection method is proposed to pick informative ROIs from only good-quality frames. We solve the space-variant distortion problem using region-based fusion based on the Dual Tree Complex Wavelet Transform (DT-CWT). We also propose an object alignment method for pre-processing the ROI since this can exhibit sig-nificant offsets and distortions between frames. Simple haze removal is used as the final step. The proposed method per-forms very well with atmospherically distorted videos and outperforms other existing methods. Index Terms — Image restoration, fusion, DT-CWT 1

SVM-based texture classification in optical coherence tomography

This paper describes a new method for automated texture classification for glaucoma detection using high resolution retinal Optical Coherence Tomography (OCT). OCT is a non-invasive technique that produces cross-sectional imagery of ocular tissue. Here, we exploit information from OCT im-ages, specifically the inner retinal layer thickness and speckle patterns, to detect glaucoma. The proposed method relies on support vector machines (SVM), while principal component analysis (PCA) is also employed to improve classification performance. Results show that texture features can improve classification accuracy over what is achieved using only layer thickness as existing methods currently do. Index Terms — classification, support vector machine, optical coherence tomography, texture 1

Automatic Generation of Matrix Element Derivatives for Tight Binding Models

Tight binding (TB) models are one approach to the quantum mechanical many particle problem. An important role in TB models is played by hopping and overlap matrix elements between the orbitals on two atoms, which of course depend on the relative positions of the atoms involved. This dependence can be expressed with the help of Slater-Koster parameters, which are usually taken from tables. Recently, a way to generate these tables automatically was published. If TB approaches are applied to simulations of the dynamics of a system, also derivatives of matrix elements can appear. In this work we give general expressions for first and second derivatives of such matrix elements. Implemented in a computer program they obviate the need to type all the required derivatives of all occuring matrix elements by hand.Comment: 11 pages, 2 figure

Atmospheric turbulence mitigation for sequences with moving objects using recursive image fusion

This paper describes a new method for mitigating the effects of atmospheric distortion on observed sequences that include large moving objects. In order to provide accurate detail from objects behind the distorting layer, we solve the space-variant distortion problem using recursive image fusion based on the Dual Tree Complex Wavelet Transform (DT-CWT). The moving objects are detected and tracked using the improved Gaussian mixture models (GMM) and Kalman filtering. New fusion rules are introduced which work on the magnitudes and angles of the DT-CWT coefficients independently to achieve a sharp image and to reduce atmospheric distortion, respectively. The subjective results show that the proposed method achieves better video quality than other existing methods with competitive speed.Comment: IEEE International Conference on Image Processing 201

An ANFIS-PI based boost converter control scheme

The PI algorithm has proven to be a popular and widely used control method, due to its relative simplicity and robustness. Despite this, the linear nature of the algorithm means it doesn't provide optimal control to non-linear systems. This paper presents a novel method of improving the performance of the PI controller using an ANFIS network to provide gain scheduling. This control scheme is applied to a Boost Converter circuit and simulated within the PSIM modelling environment. The simulation results indicate that using the ANFIS controller provides a fast system response with minimal errors even under dynamic operating conditions. The ANFIS controller is also shown to simplify the design flow in comparison to the popular Fuzzy-PI gain scheduling method

A Novel ANFIS Algorithm Architecture for FPGA Implementation

This paper presents a new architecture for the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm targeting FPGA implementation. This new architecture offers higher efficiency and scalability in comparison to the existing methods. The proposed architecture is modeled and simulated using VHDL and is targeted at a Xilinx FPGA. Existing implementation architectures are also modeled and comparisons are drawn between them in terms of both performance and logic utilization. The results show that the new architecture offers a reduction in calculation cycles of around 50% in comparison to the architecture from which it’s derived. This increase in calculation speed comes with only a modest increase in logic utilization, specifically a 2.5% increase in look-up table (LUT) usage and a 1.5% increase in flip-flop usage. The new architecture also eliminates scalability issues which can arise in the existing architectures when extra input members are required

USE OF MODERN TECHNIQUE IN PREPARING THE TECHNICAL DOCUMENTATION FOR THE REGISTRATION IN THE LAND BOOK OF A PROPERTY

The paper presents the way of drawing up the cadastral documentation for the first registration in the Land Book of a property. The total station and GNSS receivers were used as topographic devices for measurements, which offered a high accuracy of the measured data and a shortening of the time spent in the field. The data processing and the elaboration of the documentation was done through specialized programs (Toposys, Autocad). As the surveying method was used the method of closed planimetric traverse supported on known coordinate points (previously determined with GNSS technology), combined with the method of polar coordinates

FPGAs in Industrial Control Applications

The aim of this paper is to review the state-of-the-art of Field Programmable Gate Array (FPGA) technologies and their contribution to industrial control applications. Authors start by addressing various research fields which can exploit the advantages of FPGAs. The features of these devices are then presented, followed by their corresponding design tools. To illustrate the benefits of using FPGAs in the case of complex control applications, a sensorless motor controller has been treated. This controller is based on the Extended Kalman Filter. Its development has been made according to a dedicated design methodology, which is also discussed. The use of FPGAs to implement artificial intelligence-based industrial controllers is then briefly reviewed. The final section presents two short case studies of Neural Network control systems designs targeting FPGAs