Development of an in-field tree imaging system : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology at Massey University

Quality inventory information is essential for optimal resource utilisation in the forestry industry. In-field tree imaging is a method which has been proposed to improve the preharvest inventor assessment of standing trees. It involves the application of digital imaging technology to this task. The method described generates a three dimensional model of each tree through the capture of two orthogonal images from ground level. The images are captured and analysed using the "TreeScan" in-field tree imaging system. This thesis describes the design, development, and evaluation of the TreeScan system. The thesis can also be used as a technical reference for the system and as such contains appropriate technical and design detail. The TreeScan system consists of a portable computer, a custom designed high resolution scanner with integral microcontroller, a calibration rod, and custom designed processing software. Images of trees are captured using the scanner which contains a CCD line scan camera and a precision scanning mechanism. Captured images are analysed on the portable computer using customised image processing software to estimate real world tree dimensions and shape. The TreeScan system provides quantitative estimates of five tree parameters; height, sweep, stem diameter, branch diameter, and feature separation such as internodal distance. In addition to these estimates a three dimensional model is generated which can be further processed to determine the optimal stem breakdown into logs

Computations of unsteady transonic flow governed by the conservative full potential equation using an alternating direction implicit algorithm

A development was the time linearization of the density function. This linearization reduces the solution process from solving just a single equation. Two sample cases were computed. First, a one dimensional traveling shock wave was computed and compared with the analytic solution. Second, a two dimensional case was calculated for a flow field which resulted from a thickening and subsequently, thinning airfoil. The resulting flow field, which included a traveling shock wave, was compared to the flow field obtained from the low frequency, small disturbance, transonic equation

ADAPTABLE FINGERPRINT MINUTIAE EXTRACTION ALGORITHM BASED-ON CROSSING NUMBER METHOD FOR HARDWARE IMPLEMENTATION USING FPGA DEVICE

In this article. a main perspective of developing and implementing fingerprint extraction and matching algorithms as a pari of fingerprint recognition system is focused. First, developing a simple algorithm to extract fingerprint features and test this algorithm on Pc. The second thing is implementing this algorithm into FPGA devices. The major research topics on which the proposed approach is developing and modifying fingerprint extraction feature algorithm. This development and modification are using crossing number method on pixel representation value '0'. In this new proposed algorithm, it is no need a process concerning ROI segmentation and no trigonometry calculation. And specially in obtaining their parameters using Angle Calculation Block avoiding floating points calculation. As this method is local feature that usually involve with 60-100 minutiae points, makes the template is small in size. Providing FAR. FRR and EER, performs the performance evaluation of proposed algorithm. The result is an adaptable fingerprint minutiae extraction algorithm into hardware implementation with 14.05 % of EEl?, better than reference algorithm, which is 20.39 % . The computational time is 18 seconds less than a similar method, which takes 60-90 seconds just for pre-processing step. The first step of algorithm implementation in hardware environment (embedded) using FPGA Device by developing IP Core without using any soft processor is presented

Radio propagation modeling and measurements for ZigBee based indoor wireless sensor networks

The deployment of nodes in Wireless Sensor Networks (WSNs) arises as one of the biggest challenges of this field, which involves in distributing a large number of embedded systems to fulfill a specific application. The connectivity of WSNs is difficult to estimate due to the irregularity of the physical environment and affects the WSN designers? decision on deploying sensor nodes. Therefore, in this paper, a new method is proposed to enhance the efficiency and accuracy on ZigBee propagation simulation in indoor environments. The method consists of two steps: automatic 3D indoor reconstruction and 3D ray-tracing based radio simulation. The automatic 3D indoor reconstruction employs unattended image classification algorithm and image vectorization algorithm to build the environment database accurately, which also significantly reduces time and efforts spent on non-radio propagation issue. The 3D ray tracing is developed by using kd-tree space division algorithm and a modified polar sweep algorithm, which accelerates the searching of rays over the entire space. Signal propagation model is proposed for the ray tracing engine by considering both the materials of obstacles and the impact of positions along the ray path of radio. Three different WSN deployments are realized in the indoor environment of an office and the results are verified to be accurate. Experimental results also indicate that the proposed method is efficient in pre-simulation strategy and 3D ray searching scheme and is suitable for different indoor environments

Nonlinear response of dense colloidal suspensions under oscillatory shear: Mode-coupling theory and FT-rheology experiments

Using a combination of theory, experiment and simulation we investigate the nonlinear response of dense colloidal suspensions to large amplitude oscillatory shear flow. The time-dependent stress response is calculated using a recently developed schematic mode-coupling-type theory describing colloidal suspensions under externally applied flow. For finite strain amplitudes the theory generates a nonlinear response, characterized by significant higher harmonic contributions. An important feature of the theory is the prediction of an ideal glass transition at sufficiently strong coupling, which is accompanied by the discontinuous appearance of a dynamic yield stress. For the oscillatory shear flow under consideration we find that the yield stress plays an important role in determining the non linearity of the time-dependent stress response. Our theoretical findings are strongly supported by both large amplitude oscillatory (LAOS) experiments (with FT-rheology analysis) on suspensions of thermosensitive core-shell particles dispersed in water and Brownian dynamics simulations performed on a two-dimensional binary hard-disc mixture. In particular, theory predicts nontrivial values of the exponents governing the final decay of the storage and loss moduli as a function of strain amplitude which are in excellent agreement with both simulation and experiment. A consistent set of parameters in the presented schematic model achieves to jointly describe linear moduli, nonlinear flow curves and large amplitude oscillatory spectroscopy

Image morphological processing

Mathematical Morphology with applications in image processing and analysis has been becoming increasingly important in today\u27s technology. Mathematical Morphological operations, which are based on set theory, can extract object features by suitably shaped structuring elements. Mathematical Morphological filters are combinations of morphological operations that transform an image into a quantitative description of its geometrical structure based on structuring elements. Important applications of morphological operations are shape description, shape recognition, nonlinear filtering, industrial parts inspection, and medical image processing. In this dissertation, basic morphological operations, properties and fuzzy morphology are reviewed. Existing techniques for solving corner and edge detection are presented. A new approach to solve corner detection using regulated mathematical morphology is presented and is shown that it is more efficient in binary images than the existing mathematical morphology based asymmetric closing for corner detection. A new class of morphological operations called sweep mathematical morphological operations is developed. The theoretical framework for representation, computation and analysis of sweep morphology is presented. The basic sweep morphological operations, sweep dilation and sweep erosion, are defined and their properties are studied. It is shown that considering only the boundaries and performing operations on the boundaries can substantially reduce the computation. Various applications of this new class of morphological operations are discussed, including the blending of swept surfaces with deformations, image enhancement, edge linking and shortest path planning for rotating objects. Sweep mathematical morphology is an efficient tool for geometric modeling and representation. The sweep dilation/erosion provides a natural representation of sweep motion in the manufacturing processes. A set of grammatical rules that govern the generation of objects belonging to the same group are defined. Earley\u27s parser serves in the screening process to determine whether a pattern is a part of the language. Finally, summary and future research of this dissertation are provided