Dimensional Transformation Research Articles

Influencing of Coordinate Transformation on Based CGCS2000 on Topographic Map with Large Scales

Using three dimensional coordinate transformation model with 7 parameters the coordinate transformation parameters are solved. Comparing the coordinates of the kilometer grid point on topographic maps in Beijing54, Xian80 and Urban Independent Coordinate System with the observation coordinates of same point inCGCS2000, Through watching their coordinate changes the moving changes regularity on topographic maps are discovered between Beijing54 and CGCS2000, between Xian 80 and CGCS2000, Urban Independent Coordinate System and CGCS2000

펄스 레이저 스캐닝 기반 초음파 영상화 기술을 활용한 원전 배관 비파괴 진단

본 연구에서는 레이저 가진을 이용한 초음파 전파 영상 기반 배관 비파괴 검사에 관해 다룬다. 손상의 영상화를 위해 갈바노미터 기반 레이저 미러 스캐너와 Q-Switch Nd: YAG 레이저 시스템을 사용하였다. 레이저 시스템을 가진원으로 사용하면 빠른 속도로 비접촉 초음파 가진이 가능하며, 온도의 변화가 급격한 환경이나 유해 물질이 포함된 환경에서도 대상 구조물의 원거리 가진이 가능하다. 또한 공간 해상도가 높으며, 입사각이 넓어 표면 형상이 복잡한 대상 구조물도 가진이 가능하다. 본 연구에서는 이러한 레이저 시스템으로부터 생성된 유도 초음파를 단일 PZT 센서를 사용하여 계측하고, 계측된 신호는 레이저 가진점에 해당하는 좌표점에 나열함으로써 2차원 공간좌표 및 시간축을 더한 초음파 전파 영상 생성을 위한 3차원 데이터를 구성한다. 이 데이터를 시간 축에 따라 연속적으로 반복 재생하면 초음파 전파 영상을 구할 수 있다. 이 때 웨이블릿 변환을 이용하여 계측 신호의 특정 주파수 성분을 추출해냄으로써 관찰하고자 하는 특정 유도 초음파 모드를 추출할 수 있다. 이러한 일련의 과정으로부터 획득한 초음파 전파 영상 데이터를 시간-공간 영역에서 주파수-wavenumber 영역으로 변환시켜줌으로써 손상 특성을 추출할 수 있다. 본 연구에서는 손상의 진단 및 위치 추정을 위해 wavenumber 필터링 기술을 적용하였으며, 시스템 검증을 위해 다양한 배관구조물 Testbed를 대상으로 실험을 수행하였다. A noncontact nondestructive testing (NDT) method is proposed to detect the damage of pipeline structures and to identify the location of the damage. To achieve this goal, a scanning laser source actuation technique is utilized to generate a guided wave and scans a specific area to find damage location more precisely. The ND: YAG pulsed laser is used to generate Lamb wave and a piezoelectric sensor is installed to measure the structural responses. The measured responses are analyzed using three dimensional Fourier transformation (3DFT). The damage-sensitive features are extracted by wavenumber filtering based on the 3D FT. Then, flaw imaging techniques of a pipeline structures is conducted using the damage-sensitive features. Finally, the pipes with notches are investigated to verify the effectiveness and the robustness of the proposed NDT approach.

Performance Analysis of Denoising in MR Images with Double Density Dual Tree Complex Wavelets, Curvelets and Non-subsampled Contourlet Transforms

Digital images are extensively used by the medical doctors during different stages of disease diagnosis and treatment process. In the medical field, noise occurs in an image during two phases: acquisition and transmission. During the acquisition phase, noise is induced into an image, due to manufacturing defects, improper functioning of internal components, minute component failures and manual handling errors of the electronic scanning devices such as PECT/SPECT, MRI/CT scanners. Nowadays, healthcare organizations are beginning to consider cloud computing solutions for managing and sharing huge volume of medical data. This leads to the possibility of transmitting different types of medical data including CT, MR images, patient details and much more information through internet. Due to the presence of noise in the transmission channel, some unwanted signals are added to the transmitted medical data. Image denoising algorithms are employed to reduce the unwanted modifications of the pixels in an image. In this paper, the performance of denoising methods with two dimensional transformations of nonsubsampled contourlets (NSCT), curvelets, double density dual tree complex wavelets (DD-DTCWT) are compared and analysed using the image quality measures such as peak signal to noise ratio, root mean square error, structural similarity index. In

Text Extraction of Vehicle Number Plate and Document Images Using Discrete Wavelet Transform in MATLAB

Text Extraction from colour images is a challenging task in computer vision. The concept of text extraction is derived from the vehicle plate recognization and their characters extractions individually. Some examples of the applications are automatic image indexing, visual impaired people assistance or optical character reading, keyword searching in a document image. The continuous research has been done majorly that focuses on the text detection and localization in images. The paper focuses on the colour images text extraction using Two Dimensional Discrete Wavelet Transform (2D-DWT). The transform used for DWT is HAAR DWT with mathematical morphological concept. The speed of Haar DWT operates the fastest among all wavelets because its coefficients are either 1 or -1. It is one of the reasons that Haar DWT is used to detect edges of candidate text regions. Image sub bands contain both text edges and non-text edges. The work is carried out in MATLAB 12.0 image processing tool and simulated results are tested on vehicle plate text extraction and the document images.

FPGA Implementation of a High-Speed Two Dimensional Discrete Wavelet Transform

This paper proposes high-speed VLSI architecture for implementing a forward two-dimensional discrete wavelet transform (2D DWT). The architecture is based on 2D DWT mathematical formulae. A pipelined scheme is used to increase the clock rate, which allows its critical path to take only one adder delay. The proposed design enables 100% hardware use and faster computing than other 2D DWT architecture. It is easily extended to multilevel decomposition because of its regular structure. It requires N/2 by N/2 clock cycles for k-level analysis of an N by N image. The proposed architecture was coded in VerilogHDL and verified on a real time platform which uses a CMOS image sensor, a field-programmable gate array (FPGA) and a TFT-LCD panel. In the simulation, the design worked with a clock period of 132.38MHz. It can be used as an independent IP core for various real-time applications.

Geometric evolution, stability trend and electronic properties of rhenium-doped gold clusters

Based on the density functional theory with using relativistic all electron methods, this work systematically studies the geometrical structures, relative stabilities, electronic properties, and chemical hardness of AunRe (n=1–12) clusters. Low-lying energy structures include two-dimensional and three-dimensional geometries. Especially, for the lowest energy structures of AunRe (n=1–12) clusters, the planar to three dimensional transformation is found to occur at cluster size n=10 and the dopant Re atom prefers being located at highly coordinated site. After doping a Re atom, the relatively stable odd-numbered Aun+1 cluster becomes the relatively unstable odd-numbered AunRe cluster, while the relatively unstable even-numbered Aun+1 cluster becomes the relatively stable even-numbered AunRe cluster. Moreover, the presence of dopant Re atom leads to the chemical reactivity of even-numbered gold clusters becomes weaker, but the chemical reactivity of odd-numbered gold clusters turns stronger. Additionally, the spd hybridization in the Re atom of AunRe clusters is stronger than that in the corresponding Au atom of Aun+1. Au–Re bonds of AunRe clusters have stronger covalent characteristics than corresponding Au–Au bonds of Aun+1, meaning the stronger interaction between the Re and Au atoms than that between the corresponding Au and Au atoms in pure clusters.

Verification of Ganoderma (lingzhi) commercial products by Fourier Transform infrared spectroscopy and two-dimensional IR correlation spectroscopy

Ganoderma commercial products are typically based on two sources, raw material (powder form and/or spores) and extract (water and/or solvent). This study compared three types of Ganoderma commercial products using 1 Dimensional Fourier Transform infrared and second derivative spectroscopy. The analyzed spectra of Ganoderma raw material products were compared with spectra of cultivated Ganoderma raw material powder from different mushroom farms in Malaysia. The Ganoderma extract product was also compared with three types of cultivated Ganoderma extracts. Other medicinal Ganoderma contents in commercial extract product that included glucan and triterpenoid were analyzed by using FTIR and 2DIR. The results showed that water extract of cultivated Ganoderma possessed comparable spectra with that of Ganoderma product water extract. By comparing the content of Ganoderma commercial products using FTIR and 2DIR, product content profiles could be detected. In addition, the geographical origin of the Ganoderma products could be verified by comparing their spectra with Ganoderma products from known areas. This study demonstrated the possibility of developing verification tool to validate the purity of commercial medicinal herbal and mushroom products.

Testing of the Relative Precision in Local Network with Use of the Trimble Geo XR GNSS Receivers

Abstract The paper deal with testing of different GNSS measurement methods in highly accurate network for the objectives of engineering surveying. The test is comprised of a set of measurement acquired by particular GNSS methods with different observation length. For purposes of the test, an appropriate network of five points in local system was created and accurately trigonometrically measured. The result of testing is a comparison of individual methods in position using two dimensional congruent transformation and in height using one dimensional congruent transformation.

WAVELET STATISTICAL TEXTURE FEATURES WITH ORTHOGONAL OPERATORS TUMOUR CLASSIFICATION IN MAGNETIC RESONANCE IMAGING BRAIN

Tumors medically also called neoplasms are an abnormal mass of tissue resulting from uncontrolled proliferation or division of cells occurring in the human body. If such growth is located in the brain then it is called as brain tumor. Identification of such tumors is a major challenge in the field of medical science. Early identification of tumors prove to be critical as serious consequences can be averted. Its threat level depends on a combination of various factors like the type of tumor, its location, its size and its developmental stage. Tumor can occur in any part of the body. Magnetic Resonance Imaging (MRI) technique is mainly used for analyzing the brain, as the images produced are of high precision and applicability. The main objective of this study is to classify the brain MRI dataset for the existence or non existence of tumors. The proposed method uses Two Dimensional Discrete Wavelet Transform (2D-DWT) for pre-processing and further classification with orthogonal operators and SVM. The usage of 2D-DWT for pre-processing improves the classification accuracy by 2% when compared to the existing classification techniques.

A real-time borehole correction of electromagnetic wave resistivity logging while drilling

Abstract The response of electromagnetic wave logging while drilling is influenced greatly by borehole and drilling fluid resistivity when the size of borehole is relatively large and drilling fluid resistivity is low. Borehole radius and drilling fluid resistivity were introduced to obtain more accurate transformed resistivity on the basis of the commonly used resistivity transformation model. The influence of borehole was considered in the newly established three dimensional transformation model, and a new borehole correction method was proposed. The resistivity transformation database can be established by calculation according to a certain instrument, and the true resistivity is obtained by three dimensional interpolation search technology of real-time correction in practical use. The results of numerical simulation and modeling verification show that the transformed resistivity by real-time correction coincides with the resistivity corrected by charts. The method can eliminate the borehole influence, reduce calculation dimension, and improve the inversion efficiency of highly deviated and horizontal wells logging data.

A Secure Fast 2D-Discrete Fractional Fourier Transform Based Medical Image Compression Using SPIHT Algorithm with Huffman Encoder

The arrival of CT and MRI imaging in the last two decades used for analysis of various diseases in medical field. Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) sequences have become essential in healthcare systems and an integral segment of a patient’s medical record. Such medical image data needed a huge amount of resources for storage and transmission. Compression of medical images for efficient use of storage space and transmission bit rate has become a necessity. A quasigroup successfully creates an astronomical number of keys which is used to confuse the hackers in determining the original data. However, quasi group encryption is not capable in diffusing the information of the plain text. Hence, in this paper the DICOM images are encrypted using a chained Hadamard transforms and Number Theoretic Transforms to introduce diffusion along with the quasigroup transformation. A secure Fast Two Dimensional Discrete Fractional Fourier Transform (DFRFT) and a SPIHT Algorithm with Huffman Encoder is used for compress the image and it provides a secure compression of medical images as compared to the other transform. The experimental results evaluate the performance of the proposed encryption approach based on the PSNR and MSE it shows the proposed approach gives better results.

Solution of time‐fractional generalized Hirota‐Satsuma coupled KdV equation by generalised differential transformation method

PurposeIn this article, the aim is to obtain an approximate analytical solution of time‐fraction generalized Hirota‐Satsuma coupled KDV with the help of the two dimensional differential transformation method (DTM). Exact solutions can also be obtained from the known forms of the series solutions.Design/methodology/approachTwo dimensional differential transformation method (DTM) is used.FindingsIn this paper, the fractional differential transformation method is implemented to the solution of time‐fraction generalized generalized Hirota‐Satsuma coupled KDV with a number of initial and boundary values has been proved. DTM can be applied to many complicated linear and strongly nonlinear partial differential equations and does not require linearization, discretization, restrictive assumptions or perturbation. The presented method is a numerical method based on the generalised Taylor series expansion which constructs an analytical solution in the form of a polynomial.Originality/valueThis is an original work in which the results indicate that the method is powerful and significant for solving time‐fraction generalized generalized Hirota‐Satsuma coupled KDV type differential equations.

ChemInform Abstract: Nanoparticle Assemblies: Dimensional Transformation of Nanomaterials and Scalability

AbstractReview: 107 refs.

Digital image scrambling technology based on three dimensional sub-affine transformation

In order to improve the security and flexibility of digital image information hiding,adopting the theory of sub-affine transformation,a new image encryption algorithm based on three dimensional sub-affine transformation was designed.By analyzing the constraints of three dimensional sub-affine transformation,according to the relation between variables and randomness of variables,a rapid construction method of three dimensional sub-affine transformation was given.Three color components of each pixel in the color space chose different ways to transform for achieving image scrambling,and its periodicity was discussed,for proposing the concept of singularity point and fake period.The experimental analysis shows that the algorithm has good effect of scrambling,larger key space,flexible encryption,and high security.And its diffusion and disturbance are ideal.

Forensic Face Sketch Recognition Using Computer Vision

Now - a - days need for technologies for identification, detection and recognition of suspects has increased. One of the most common biometric techniques is face recognition, since face is the convenient way used by the people to identify each - other. Understanding how humans recognize face sketches drawn by artists is of significant value to both criminal investigators and forensic researchers in Computer Vision. However studies say that hand - drawn face sketches are still very limited in terms of artists and number of sketches because after any incident a forensic artist prepares a victims sketches on behalf of the descripti on provided by an eyewitness. Sometimes suspects used special mask to hide some common features of faces like nose, eyes, lips, face - color etc. but the outliner features of face biometrics one could never hide. In this work, I concentrated on some specific facial geometric feature which could be used to calculate some ratios of similarities from the template photograph database against the forensic sketches. This paper describes the design of a system for forensic face sketch recognition by a computer visi on approach like Two - Dimensional Discrete Cosine Transform (2D - DCT) and the Self - Organizing Map (SOM) Neural Network simulated in MATLAB.

Dimensional transformation in tests of spatial and environmental cognition

In previous research, it has been argued that spatial performance on psychometric tests might be accounted for, in part, by the need for test-takers to transform mentally two-dimensional (2-D) test items into a three-dimensional (3-D) representation. With this in mind, the Landscape Perception Test (LPT) was designed to isolate the 2-D to 3-D (and vice versa) transformational aspect of spatial cognition. Gender differences were used as an indirect means to examine the contribution of the 2-D to 3-D transformation to spatial performance. Since the LPT was designed by means of an image relevant to geospatial cognition, measures of environmental cognition, as well as experience in various activities, were also examined. One hundred thirty undergraduate students (66 females and 64 males) completed the Childhood Activities Questionnaire, the Santa Barbara Sense of Direction Test, the Visualization of Views (VV) Test, the Perspective Taking/Spatial Orientation Test, and the LPT. Results showed higher scores for men than for women on LPT items requiring 2-D to 3-D conversion (LPT23), but not on those requiring the reverse operation. In addition, only the LPT23 produced significant indirect effects of gender on VV Test performance. Performance on the tests was also correlated with environmental cognition and previous experience with spatial activities. The results suggest that dimensional transformation might be a factor significantly contributing to spatial performance. Psychometric aspects of the LPT are also discussed.

A theorem on entire four dimensional summability methods

This paper introduce the following concept of double entire double sequences. Let x={xk,l} be a double sequence of complex numbers. Then the double sequence {x} is entire provided that∑k,l=0,0∞,∞xk,lpkql<∞for every positive integers p and q. Using this definition I will also introduce the notion Four dimensional entire summability method. The author uses the notions to prove directly necessary and sufficient condition which ensure that a four dimensional transformation is entire.

Recognition of Tamil Handwritten Characters using Daubechies Wavelet Transforms and Feed-Forward Backpropagation Network

This article suggests wavelet transform based feature extraction technique for extracting robust features from Tamil handwritten characters. The algorithm uses feed-forward back propagation neural network as the classifier. It presents the relevant features of Tamil script and describes various techniques used for character recognition. In common, all the pattern recognition tasks focus on extracting more differentiating features. This is the most important and complicated job. The proposed system concentrates on two dimensional discrete wavelet transformations for extraction of features. For multiresolution analysis of images, Wavelet Transform is used. This capability can be used to study the character image in different frequency bands. Localized basis functions of WT are used for extracting localized features of a character image. This enables us to obtain more distinct traits as features for each character. Feed forward back propagation neural network is one of the general neural network architectures and this architecture can be applied to many different tasks and is very popular.

A unified maximum entropy method via spline functions for Frobenius-Perron operators

We present a general frame of finite element maximum entropy methods for the computation of a stationary density of Frobenius-Perron operators associated with one dimensional transformations, based on spline function approximations. This gives a unified numerical approach to the density recovery for this class of positive operators by combining the principle of maximum entropy with the idea of finite elements. The norm convergence of the method is proved and the numerical results with the piecewise cubic method show its fast convergence.

Quantitative analysis of the magnetic domain structure in polycrystalline La0.7Sr0.3MnO3thin films by magnetic force microscopy

The nanoscale magnetic domain structure of the polycrystalline La(0.7)Sr(0.3)MnO(3) granular thin films was imaged with a developed magnetic force microscopy technique by simultaneously detecting both the perpendicular and in-plane components of magnetic field gradients during the same scan of the tip oscillation. The characteristics of both the perpendicular and in-plane magnetic field gradient at the grain edges or the nonmagnetic grain boundary phase for LSMO films were demonstrated and can be used to evaluate the magnetic domain structure and magnetic isolation between neighboring grains. A two dimensional signal transformation algorithm to reconstruct the in-plane magnetization distribution of the polycrystalline LSMO thin films from the measured raw MFM images with the aid of the deconvolution technique was presented. The comparison between the experimental and simulated MFM images indicates that the magnetic grains or clusters are in the single domain (SD) or multi-domain (MD) state with the magnetic moments parallel or anti-parallel to the effective magnetic field of each grain, possibly due to the need for minimizing the total energy. The quantitative interpretation of the magnetic domain structure indicates that the large magnetoresistance in the studied LSMO films is mainly due to tunnel effect and scattering of conducted electrons at the nonmagnetic grain boundary phase related to the different configurations of magnetic domain states between neighboring grains.