4,141 research outputs found
Map online system using internet-based image catalogue
Digital maps carry along its geodata information such as coordinate that is important in one particular topographic and thematic map. These geodatas are meaningful especially in military field. Since the maps carry along this information, its makes the size of the images is too big. The bigger size, the bigger storage is required to allocate the image file. It also can cause longer loading time. These conditions make it did not suitable to be applied in image catalogue approach via internet environment. With compression techniques, the image size can be reduced and the quality of the image is still guaranteed without much changes. This report is paying attention to one of the image compression technique using wavelet technology. Wavelet technology is much batter than any other image compression technique nowadays. As a result, the compressed images applied to a system called Map Online that used Internet-based Image Catalogue approach. This system allowed user to buy map online. User also can download the maps that had been bought besides using the searching the map. Map searching is based on several meaningful keywords. As a result, this system is expected to be used by Jabatan Ukur dan Pemetaan Malaysia (JUPEM) in order to make the organization vision is implemented
Multiple bottlenecks sorting criterion at initial sequence in solving permutation flow shop scheduling problem
This paper proposes a heuristic that introduces the
application of bottleneck-based concept at the beginning of an initial sequence
determination with the objective of makespan minimization. Earlier studies
found that the scheduling activity become complicated when dealing with
machine, m greater than 2, known as non-deterministic polynomial-time
hardness (NP-hard). To date, the Nawaz-Enscore-Ham (NEH) algorithm is
still recognized as the best heuristic in solving makespan problem in
scheduling environment. Thus, this study treated the NEH heuristic as the
highest ranking and most suitable heuristic for evaluation purpose since it is
the best performing heuristic in makespan minimization. This study used the
bottleneck-based approach to identify the critical processing machine which
led to high completion time. In this study, an experiment involving machines
(m =4) and n-job (n = 6, 10, 15, 20) was simulated in Microsoft Excel Simple
Programming to solve the permutation flowshop scheduling problem. The
overall computational results demonstrated that the bottleneck machine M4
performed the best in minimizing the makespan for all data set of problems
Machine Analysis of Facial Expressions
No abstract
Continuous Wavelet Transform and Hidden Markov Model Based Target Detection
Standard tracking filters perform target detection process by comparing the sensor output signal with a predefined threshold. However, selecting the detection threshold is of great importance and a wrongly selected threshold causes two major problems. The first problem occurs when the selected threshold is too low which results in increased false alarm rate. The second problem arises when the selected threshold is too high resulting in missed detection. Track-before-detect (TBD) techniques eliminate the need for a detection threshold and provide detecting and tracking targets with lower signal-to-noise ratios than standard methods. Although TBD techniques eliminate the need for detection threshold at sensorâs signal processing stage, they often use tuning thresholds at the output of the filtering stage. This paper presents a Continuous Wavelet Transform (CWT) and Hidden Markov Model (HMM) based target detection method for employing with TBD techniques which does not employ any thresholding
Retinal Vessel Segmentation Using the 2-D Morlet Wavelet and Supervised Classification
We present a method for automated segmentation of the vasculature in retinal
images. The method produces segmentations by classifying each image pixel as
vessel or non-vessel, based on the pixel's feature vector. Feature vectors are
composed of the pixel's intensity and continuous two-dimensional Morlet wavelet
transform responses taken at multiple scales. The Morlet wavelet is capable of
tuning to specific frequencies, thus allowing noise filtering and vessel
enhancement in a single step. We use a Bayesian classifier with
class-conditional probability density functions (likelihoods) described as
Gaussian mixtures, yielding a fast classification, while being able to model
complex decision surfaces and compare its performance with the linear minimum
squared error classifier. The probability distributions are estimated based on
a training set of labeled pixels obtained from manual segmentations. The
method's performance is evaluated on publicly available DRIVE and STARE
databases of manually labeled non-mydriatic images. On the DRIVE database, it
achieves an area under the receiver operating characteristic (ROC) curve of
0.9598, being slightly superior than that presented by the method of Staal et
al.Comment: 9 pages, 7 figures and 1 table. Accepted for publication in IEEE
Trans Med Imag; added copyright notic
Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images
We present a novel kernel regression framework for smoothing scalar surface
data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel
constructed from the eigenfunctions, we formulate a new bivariate kernel
regression framework as a weighted eigenfunction expansion with the heat kernel
as the weights. The new kernel regression is mathematically equivalent to
isotropic heat diffusion, kernel smoothing and recently popular diffusion
wavelets. Unlike many previous partial differential equation based approaches
involving diffusion, our approach represents the solution of diffusion
analytically, reducing numerical inaccuracy and slow convergence. The numerical
implementation is validated on a unit sphere using spherical harmonics. As an
illustration, we have applied the method in characterizing the localized growth
pattern of mandible surfaces obtained in CT images from subjects between ages 0
and 20 years by regressing the length of displacement vectors with respect to
the template surface.Comment: Accepted in Medical Image Analysi
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