Search results for: competency matching
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 391

Search results for: competency matching

331 Matching-Based Cercospora Leaf Spot Detection in Sugar Beet

Authors: Rong Zhou, Shun’ich Kaneko, Fumio Tanaka, Miyuki Kayamori, Motoshige Shimizu

Abstract:

In this paper, we propose a robust disease detection method, called adaptive orientation code matching (Adaptive OCM), which is developed from a robust image registration algorithm: orientation code matching (OCM), to achieve continuous and site-specific detection of changes in plant disease. We use two-stage framework for realizing our research purpose; in the first stage, adaptive OCM was employed which could not only realize the continuous and site-specific observation of disease development, but also shows its excellent robustness for non-rigid plant object searching in scene illumination, translation, small rotation and occlusion changes and then in the second stage, a machine learning method of support vector machine (SVM) based on a feature of two dimensional (2D) xy-color histogram is further utilized for pixel-wise disease classification and quantification. The indoor experiment results demonstrate the feasibility and potential of our proposed algorithm, which could be implemented in real field situation for better observation of plant disease development.

Keywords: Cercospora Leaf Spot (CLS), Disease detection, Image processing, Orientation Code Matching (OCM), Support Vector Machine (SVM).

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330 Generation of Photo-Mosaic Images through Block Matching and Color Adjustment

Authors: Hae-Yeoun Lee

Abstract:

Mosaic refers to a technique that makes image by gathering lots of small materials in various colors. This paper presents an automatic algorithm that makes the photo-mosaic image using photos. The algorithm is composed of 4 steps: partition and feature extraction, block matching, redundancy removal and color adjustment. The input image is partitioned in the small block to extract feature. Each block is matched to find similar photo in database by comparing similarity with Euclidean difference between blocks. The intensity of the block is adjusted to enhance the similarity of image by replacing the value of light and darkness with that of relevant block. Further, the quality of image is improved by minimizing the redundancy of tiles in the adjacent blocks. Experimental results support that the proposed algorithm is excellent in quantitative analysis and qualitative analysis.

Keywords: Photo-mosaic, Euclidean distance, Block matching, Intensity adjustment.

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329 High-Accuracy Satellite Image Analysis and Rapid DSM Extraction for Urban Environment Evaluations (Tripoli-Libya)

Authors: Abdunaser Abduelmula, Maria Luisa M. Bastos, José A. Gonçalves

Abstract:

Modelling of the earth's surface and evaluation of urban environment, with 3D models, is an important research topic. New stereo capabilities of high resolution optical satellites images, such as the tri-stereo mode of Pleiades, combined with new image matching algorithms, are now available and can be applied in urban area analysis. In addition, photogrammetry software packages gained new, more efficient matching algorithms, such as SGM, as well as improved filters to deal with shadow areas, can achieve more dense and more precise results. This paper describes a comparison between 3D data extracted from tri-stereo and dual stereo satellite images, combined with pixel based matching and Wallis filter. The aim was to improve the accuracy of 3D models especially in urban areas, in order to assess if satellite images are appropriate for a rapid evaluation of urban environments. The results showed that 3D models achieved by Pleiades tri-stereo outperformed, both in terms of accuracy and detail, the result obtained from a Geo-eye pair. The assessment was made with reference digital surface models derived from high resolution aerial photography. This could mean that tri-stereo images can be successfully used for the proposed urban change analyses.

Keywords: 3D Models, Environment, Matching, Pleiades.

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328 On the Optimal Number of Smart Dust Particles

Authors: Samee Ullah Khan, C. Ardil

Abstract:

Smart Dust particles, are small smart materials used for generating weather maps. We investigate question of the optimal number of Smart Dust particles necessary for generating precise, computationally feasible and cost effective 3–D weather maps. We also give an optimal matching algorithm for the generalized scenario, when there are N Smart Dust particles and M ground receivers.

Keywords: Remote sensing, smart dust, matching, optimization.

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327 A Survey of Model Comparison Strategies and Techniques in Model Driven Engineering

Authors: Junaid Rashid, Waqar Mehmood, Muhammad Wasif Nisar

Abstract:

This survey paper shows the recent state of model comparison as it’s applies to Model Driven engineering. In Model Driven Engineering to calculate the difference between the models is a very important and challenging task. There are number of tasks involved in model differencing that firstly starts with identifying and matching the elements of the model. In this paper, we discuss how model matching is accomplished, the strategies, techniques and the types of the model. We also discuss the future direction. We found out that many of the latest model comparison strategies are geared near enabling Meta model and similarity based matching. Therefore model versioning is the most dominant application of the model comparison. Recently to work on comparison for versioning has begun to deteriorate, giving way to different applications. Ultimately there is wide change among the tools in the measure of client exertion needed to perform model comparisons, as some require more push to encourage more sweeping statement and expressive force.

Keywords: Model comparison, model clone detection, model versioning, EMF Model, model diff.

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326 Research Trend Analysis – A Sample in the Field of Information Systems

Authors: Hei-Chia Wang, Wei-Pin Chiu

Abstract:

As research performance in academia is treated as one of indices for national competency, many countries devote much attention and resources to increasing their research performance. Understand the research trend is the basic step to improve the research performance. The goal of this research is to design an analysis system to evaluate research trends from analyzing data from different countries. In this paper, information system researches in Taiwan and other countries, including Asian countries and prominent countries represented by the Group of Eight (G8) is used as example. Our research found the trends are varied in different countries. Our research suggested that Taiwan-s scholars can pay more attention to interdisciplinary applications and try to increase their collaboration with other countries, in order to increase Taiwan's competency in the area of information science.

Keywords: Bibliometric analysis, research trend, scientometric analysis.

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325 Joint Adaptive Block Matching Search (JABMS) Algorithm

Authors: V.K.Ananthashayana, Pushpa.M.K

Abstract:

In this paper a new Joint Adaptive Block Matching Search (JABMS) algorithm is proposed to generate motion vector and search a best match macro block by classifying the motion vector movement based on prediction error. Diamond Search (DS) algorithm generates high estimation accuracy when motion vector is small and Adaptive Rood Pattern Search (ARPS) algorithm can handle large motion vector but is not very accurate. The proposed JABMS algorithm which is capable of considering both small and large motions gives improved estimation accuracy and the computational cost is reduced by 15.2 times compared with Exhaustive Search (ES) algorithm and is 1.3 times less compared with Diamond search algorithm.

Keywords: Adaptive rood pattern search, Block matching, Diamond search, Joint Adaptive search, Motion estimation.

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324 3D Liver Segmentation from CT Images Using a Level Set Method Based on a Shape and Intensity Distribution Prior

Authors: Nuseiba M. Altarawneh, Suhuai Luo, Brian Regan, Guijin Tang

Abstract:

Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity, and specificity.

Keywords: Bhattacharyya distance, distance regularized level set (DRLS) model, liver segmentation, level set method.

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323 Fingerprint Verification System Using Minutiae Extraction Technique

Authors: Manvjeet Kaur, Mukhwinder Singh, Akshay Girdhar, Parvinder S. Sandhu

Abstract:

Most fingerprint recognition techniques are based on minutiae matching and have been well studied. However, this technology still suffers from problems associated with the handling of poor quality impressions. One problem besetting fingerprint matching is distortion. Distortion changes both geometric position and orientation, and leads to difficulties in establishing a match among multiple impressions acquired from the same finger tip. Marking all the minutiae accurately as well as rejecting false minutiae is another issue still under research. Our work has combined many methods to build a minutia extractor and a minutia matcher. The combination of multiple methods comes from a wide investigation into research papers. Also some novel changes like segmentation using Morphological operations, improved thinning, false minutiae removal methods, minutia marking with special considering the triple branch counting, minutia unification by decomposing a branch into three terminations, and matching in the unified x-y coordinate system after a two-step transformation are used in the work.

Keywords: Biometrics, Minutiae, Crossing number, False Accept Rate (FAR), False Reject Rate (FRR).

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322 Tool for Fast Detection of Java Code Snippets

Authors: Tomáš Bublík, Miroslav Virius

Abstract:

This paper presents general results on the Java source code snippet detection problem. We propose the tool which uses graph and subgraph isomorphism detection. A number of solutions for all of these tasks have been proposed in the literature. However, although that all these solutions are really fast, they compare just the constant static trees. Our solution offers to enter an input sample dynamically with the Scripthon language while preserving an acceptable speed. We used several optimizations to achieve very low number of comparisons during the matching algorithm.

Keywords: AST, Java, tree matching, Scripthon, source code recognition

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321 Communicative Competence in Technical Oral Presentation: That “Magic“ Perceived by ESL Educators versus Content Experts

Authors: Ena Bhattacharyya, Zullina H. Shaari

Abstract:

Till date, English as a Second Language (ESL) educators involved in teaching language and communication to engineering students face an uphill task in developing graduate communicative competency. This challenge is accentuated by the apparent lack of English for Specific Purposes (ESP) materials for engineering students in the engineering curriculum. As such, most ESL educators are forced to play multiple roles. They don tasks such as curriculum designers, material writers and teachers with limited knowledge of the disciplinary content. Previous research indicates that prospective professional engineers should possess some sub-sets of competency: technical, linguistic oral immediacy, meta-cognitive and rhetorical explanatory competence. Another study revealed that engineering students need to be equipped with technical and linguistic oral immediacy competence. However, little is known whether these competency needs are in line with the educators- perceptions of communicative competence. This paper examines the best mix of communicative competence subsets that create the magic for engineering students in technical oral presentations. For the purpose of this study, two groups of educators were interviewed. These educators were language and communication lecturers involved in teaching a speaking course and content experts who assess students- technical oral presentations at tertiary level. The findings indicate that these two groups differ in their perceptions

Keywords: Communicative competence, Content experts, Educators, Technical Oral Presentations

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320 Effective Image and Video Error Concealment using RST-Invariant Partial Patch Matching Model and Exemplar-based Inpainting

Authors: Shiraz Ahmad, Zhe-Ming Lu

Abstract:

An effective visual error concealment method has been presented by employing a robust rotation, scale, and translation (RST) invariant partial patch matching model (RSTI-PPMM) and exemplar-based inpainting. While the proposed robust and inherently feature-enhanced texture synthesis approach ensures the generation of excellent and perceptually plausible visual error concealment results, the outlier pruning property guarantees the significant quality improvements, both quantitatively and qualitatively. No intermediate user-interaction is required for the pre-segmented media and the presented method follows a bootstrapping approach for an automatic visual loss recovery and the image and video error concealment.

Keywords: Exemplar-based image and video inpainting, outlierpruning, RST-invariant partial patch matching model (RSTI-PPMM), visual error concealment.

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319 Strategic Regional Identity for Health and Wellness Lodging

Authors: Pongsiri K.

Abstract:

This research aimed to study the competency of health and wellness hotels and resorts in developing use the local natural resources and wisdom to conform to the national health and wellness tourism (HWT) strategy by comparing two independent samples, from Aumpur Muang, Ranong province and Aumpur Muang, Chiangmai province. And also study in the suggestive direct path to lead the organization to the sustainable successful. This research was conduct by using mix methodology; both quantitative and qualitative data were used. The data of competency of health and wellness hotels and resorts (HWHR) in developing use the local natural resources for HWT promoting were collected via 300 set of questionnaires, from 6 hotels and resorts in 2 areas, 3 places from Aumpur Muang, Ranong province and another 3 from Aumpur Muang, Chiangmai province. Thestudy of HWHR’s competency in developing use the local natural resources and wisdom to conform to the national HWT strategycan be divided into fourmain areas, food and beverages service, tourism activity, environmental service, and value adding. The total competency of the Chiangmai sample is importantly scoredp. value 0.01 higher than the Ranong one while the area of safety, Chiangmai’s competency is importantly scored 0.05 higher than the Ranong’scompetency. Others were rated not differently. Since Chiangmai perform better, then it can be a role model in developing HTHR or HWT destination. From the part of qualitative research, content analysis of business contents and its environments were analyzed. The four stages of strategic development and plans, from the smallest scale to the largest scale such a national base were discussed. The HWT: Evolution model and strategy for lodging Business were suggested. All those stages must work harmoniously together. The distinctive result illustrates the need of human resource development as the key point to create the identity of Thainess on Health and wellness service providing. This will add-on the value of services and differentiates ourselves from other competitors. The creative of Thailand’s health and wellness brand possibly increase loyalty customers which agreed to be a path of sustainable development.

Keywords: Health and Wellness Tourism (HWT), Strategic Analysis, Health and Wellness Hotels and Resorts (HWHR), Lodging Firms.

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318 N-Sun Decomposition of Complete, Complete Bipartite and Some Harary Graphs

Authors: R. Anitha, R. S. Lekshmi

Abstract:

Graph decompositions are vital in the study of combinatorial design theory. A decomposition of a graph G is a partition of its edge set. An n-sun graph is a cycle Cn with an edge terminating in a vertex of degree one attached to each vertex. In this paper, we define n-sun decomposition of some even order graphs with a perfect matching. We have proved that the complete graph K2n, complete bipartite graph K2n, 2n and the Harary graph H4, 2n have n-sun decompositions. A labeling scheme is used to construct the n-suns.

Keywords: Decomposition, Hamilton cycle, n-sun graph, perfect matching, spanning tree.

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317 Face Recognition Using Eigen face Coefficients and Principal Component Analysis

Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Samriti Jindal, Inderpreet Kaur, Shilpi Kumari

Abstract:

Face Recognition is a field of multidimensional applications. A lot of work has been done, extensively on the most of details related to face recognition. This idea of face recognition using PCA is one of them. In this paper the PCA features for Feature extraction are used and matching is done for the face under consideration with the test image using Eigen face coefficients. The crux of the work lies in optimizing Euclidean distance and paving the way to test the same algorithm using Matlab which is an efficient tool having powerful user interface along with simplicity in representing complex images.

Keywords: Eigen Face, Multidimensional, Matching, PCA.

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316 Automatic Detection of Syllable Repetition in Read Speech for Objective Assessment of Stuttered Disfluencies

Authors: K. M. Ravikumar, Balakrishna Reddy, R. Rajagopal, H. C. Nagaraj

Abstract:

Automatic detection of syllable repetition is one of the important parameter in assessing the stuttered speech objectively. The existing method which uses artificial neural network (ANN) requires high levels of agreement as prerequisite before attempting to train and test ANNs to separate fluent and nonfluent. We propose automatic detection method for syllable repetition in read speech for objective assessment of stuttered disfluencies which uses a novel approach and has four stages comprising of segmentation, feature extraction, score matching and decision logic. Feature extraction is implemented using well know Mel frequency Cepstra coefficient (MFCC). Score matching is done using Dynamic Time Warping (DTW) between the syllables. The Decision logic is implemented by Perceptron based on the score given by score matching. Although many methods are available for segmentation, in this paper it is done manually. Here the assessment by human judges on the read speech of 10 adults who stutter are described using corresponding method and the result was 83%.

Keywords: Assessment, DTW, MFCC, Objective, Perceptron, Stuttering.

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315 Human Verification in a Video Surveillance System Using Statistical Features

Authors: Sanpachai Huvanandana

Abstract:

A human verification system is presented in this paper. The system consists of several steps: background subtraction, thresholding, line connection, region growing, morphlogy, star skelatonization, feature extraction, feature matching, and decision making. The proposed system combines an advantage of star skeletonization and simple statistic features. A correlation matching and probability voting have been used for verification, followed by a logical operation in a decision making stage. The proposed system uses small number of features and the system reliability is convincing.

Keywords: Human verification, object recognition, videounderstanding, segmentation.

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314 Shape-Based Image Retrieval Using Shape Matrix

Authors: C. Sheng, Y. Xin

Abstract:

Retrieval image by shape similarity, given a template shape is particularly challenging, owning to the difficulty to derive a similarity measurement that closely conforms to the common perception of similarity by humans. In this paper, a new method for the representation and comparison of shapes is present which is based on the shape matrix and snake model. It is scaling, rotation, translation invariant. And it can retrieve the shape images with some missing or occluded parts. In the method, the deformation spent by the template to match the shape images and the matching degree is used to evaluate the similarity between them.

Keywords: shape representation, shape matching, shape matrix, deformation

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313 Enhanced Bidirectional Selection Sort

Authors: Jyoti Dua

Abstract:

An algorithm is a well-defined procedure that takes some input in the form of some values, processes them and gives the desired output. It forms the basis of many other algorithms such as searching, pattern matching, digital filters etc., and other applications have been found in database systems, data statistics and processing, data communications and pattern matching. This paper introduces algorithmic “Enhanced Bidirectional Selection” sort which is bidirectional, stable. It is said to be bidirectional as it selects two values smallest from the front and largest from the rear and assigns them to their appropriate locations thus reducing the number of passes by half the total number of elements as compared to selection sort.

Keywords: Bubble sort, cocktail sort, selection sort, heap sort.

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312 The Development of an Integrity Cultivating Module in School-Based Assessment among Malaysian Teachers: A Research Methodology

Authors: Eftah Bte. Moh Hj Abdullah, Abd Aziz Bin Abd Shukor, Norazilawati Binti Abdullah, Rahimah Adam, Othman Bin Lebar

Abstract:

The competency and integrity required for better understanding and practice of School-based Assessment (PBS) comes not only from the process, but also in providing the support or ‘scaffolding’ for teachers to recognize the student as a learner, improve their self-assessment skills, understanding of the daily teaching plan and its constructive alignment of the curriculum, pedagogy and assessment. The cultivation of integrity in PBS among the teachers is geared towards encouraging them to become committed and dedicated in implementing assessments in a serious, efficient manner, thus moving away from the usual teacher-focused approach to the student-focused approach. The teachers show their integrity via their professional commitment, responsibility and actions. The module based on the cultivation of integrity in PBS among Malaysian teachers aims to broaden the guidance support for teachers (embedded in the training), which consists of various domains to enable better evaluation of complex assessment tasks and the construction of suitable instrument for measuring the relevant cognitive, affective and psychomotor domains to describe the students’ achievement. The instrument for integrity cultivation in PBS has been developed and validated for measuring the effectiveness of the module constructed. This module is targeted towards assisting the staff in the Education Ministry, especially the principal trainers, teachers, headmasters and education officers to acquire effective intervention for improving the PBS assessors’ integrity and competency.

Keywords: School-based assessment, Assessment competency Integrity cultivation, Professional commitment, Module.

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311 Indoor Localization by Pattern Matching Method Based On Extended Database

Authors: Gyumin Hwang, Jihong Lee

Abstract:

This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.

Keywords: Chirp Spread Spectrum (CSS), Indoor Localization, Pattern-Matching, Time of Arrival (ToA), Multi-Path, Mahalanobis Distance, Reception Rate, Simultaneous Localization and Mapping (SLAM), Laser Range Finder (LRF).

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310 Distributed Relay Selection and Channel Choice in Cognitive Radio Network

Authors: Hao He, Shaoqian Li

Abstract:

In this paper, we study the cooperative communications where multiple cognitive radio (CR) transmit-receive pairs competitive maximize their own throughputs. In CR networks, the influences of primary users and the spectrum availability are usually different among CR users. Due to the existence of multiple relay nodes and the different spectrum availability, each CR transmit-receive pair should not only select the relay node but also choose the appropriate channel. For this distributed problem, we propose a game theoretic framework to formulate this problem and we apply a regret-matching learning algorithm which is leading to correlated equilibrium. We further formulate a modified regret-matching learning algorithm which is fully distributed and only use the local information of each CR transmit-receive pair. This modified algorithm is more practical and suitable for the cooperative communications in CR network. Simulation results show the algorithm convergence and the modified learning algorithm can achieve comparable performance to the original regretmatching learning algorithm.

Keywords: cognitive radio, cooperative communication, relay selection, channel choice, regret-matching learning, correlated equilibrium.

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309 A New Traffic Pattern Matching for DDoS Traceback Using Independent Component Analysis

Authors: Yuji Waizumi, Tohru Sato, Yoshiaki Nemoto

Abstract:

Recently, Denial of Service(DoS) attacks and Distributed DoS(DDoS) attacks which are stronger form of DoS attacks from plural hosts have become security threats on the Internet. It is important to identify the attack source and to block attack traffic as one of the measures against these attacks. In general, it is difficult to identify them because information about the attack source is falsified. Therefore a method of identifying the attack source by tracing the route of the attack traffic is necessary. A traceback method which uses traffic patterns, using changes in the number of packets over time as criteria for the attack traceback has been proposed. The traceback method using the traffic patterns can trace the attack by matching the shapes of input traffic patterns and the shape of output traffic pattern observed at a network branch point such as a router. The traffic pattern is a shapes of traffic and unfalsifiable information. The proposed trace methods proposed till date cannot obtain enough tracing accuracy, because they directly use traffic patterns which are influenced by non-attack traffics. In this paper, a new traffic pattern matching method using Independent Component Analysis(ICA) is proposed.

Keywords: Distributed Denial of Service, Independent Component Analysis, Traffic pattern

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308 Genetic Algorithm and Padé-Moment Matching for Model Order Reduction

Authors: Shilpi Lavania, Deepak Nagaria

Abstract:

A mixed method for model order reduction is presented in this paper. The denominator polynomial is derived by matching both Markov parameters and time moments, whereas numerator polynomial derivation and error minimization is done using Genetic Algorithm. The efficiency of the proposed method can be investigated in terms of closeness of the response of reduced order model with respect to that of higher order original model and a comparison of the integral square error as well.

Keywords: Model Order Reduction (MOR), control theory, Markov parameters, time moments, genetic algorithm, Single Input Single Output (SISO).

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307 Matching Pursuit based Removal of Cardiac Pulse-Related Artifacts in EEG/fMRI

Authors: Rainer Schneider, Stephan Lau, Levin Kuhlmann, Simon Vogrin, Maciej Gratkowski, Mark Cook, Jens Haueisen

Abstract:

Cardiac pulse-related artifacts in the EEG recorded simultaneously with fMRI are complex and highly variable. Their effective removal is an unsolved problem. Our aim is to develop an adaptive removal algorithm based on the matching pursuit (MP) technique and to compare it to established methods using a visual evoked potential (VEP). We recorded the VEP inside the static magnetic field of an MR scanner (with artifacts) as well as in an electrically shielded room (artifact free). The MP-based artifact removal outperformed average artifact subtraction (AAS) and optimal basis set removal (OBS) in terms of restoring the EEG field map topography of the VEP. Subsequently, a dipole model was fitted to the VEP under each condition using a realistic boundary element head model. The source location of the VEP recorded inside the MR scanner was closest to that of the artifact free VEP after cleaning with the MP-based algorithm as well as with AAS. While none of the tested algorithms offered complete removal, MP showed promising results due to its ability to adapt to variations of latency, frequency and amplitude of individual artifact occurrences while still utilizing a common template.

Keywords: matching pursuit, ballistocardiogram, artifactremoval, EEG/fMRI.

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306 Improved Feature Processing for Iris Biometric Authentication System

Authors: Somnath Dey, Debasis Samanta

Abstract:

Iris-based biometric authentication is gaining importance in recent times. Iris biometric processing however, is a complex process and computationally very expensive. In the overall processing of iris biometric in an iris-based biometric authentication system, feature processing is an important task. In feature processing, we extract iris features, which are ultimately used in matching. Since there is a large number of iris features and computational time increases as the number of features increases, it is therefore a challenge to develop an iris processing system with as few as possible number of features and at the same time without compromising the correctness. In this paper, we address this issue and present an approach to feature extraction and feature matching process. We apply Daubechies D4 wavelet with 4 levels to extract features from iris images. These features are encoded with 2 bits by quantizing into 4 quantization levels. With our proposed approach it is possible to represent an iris template with only 304 bits, whereas existing approaches require as many as 1024 bits. In addition, we assign different weights to different iris region to compare two iris templates which significantly increases the accuracy. Further, we match the iris template based on a weighted similarity measure. Experimental results on several iris databases substantiate the efficacy of our approach.

Keywords: Iris recognition, biometric, feature processing, patternrecognition, pattern matching.

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305 Efficient Block Matching Algorithm for Motion Estimation

Authors: Zong Chen

Abstract:

Motion estimation is a key problem in video processing and computer vision. Optical flow motion estimation can achieve high estimation accuracy when motion vector is small. Three-step search algorithm can handle large motion vector but not very accurate. A joint algorithm was proposed in this paper to achieve high estimation accuracy disregarding whether the motion vector is small or large, and keep the computation cost much lower than full search.

Keywords: Motion estimation, Block Matching, Optical flow, Three step search.

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304 A Fast HRRP Synthesis Algorithm with Sensing Dictionary in GTD Model

Authors: R. Fan, Q. Wan, H. Chen, Y.L. Liu, Y.P. Liu

Abstract:

In the paper, a fast high-resolution range profile synthetic algorithm called orthogonal matching pursuit with sensing dictionary (OMP-SD) is proposed. It formulates the traditional HRRP synthetic to be a sparse approximation problem over redundant dictionary. As it employs a priori that the synthetic range profile (SRP) of targets are sparse, SRP can be accomplished even in presence of data lost. Besides, the computation complexity decreases from O(MNDK) flops for OMP to O(M(N + D)K) flops for OMP-SD by introducing sensing dictionary (SD). Simulation experiments illustrate its advantages both in additive white Gaussian noise (AWGN) and noiseless situation, respectively.

Keywords: GTD-based model, HRRP, orthogonal matching pursuit, sensing dictionary.

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303 The Development of Flying Type Moving Robot Using Image Processing

Authors: Suriyon Tansuriyavong, Yuuta Suzuki, Boonmee Choompol

Abstract:

Wheel-running type moving robot has the restriction on the moving range caused by obstacles or stairs. Solving this weakness, we studied the development of moving robot using airship. Our airship robot moves by recognizing arrow marks on the path. To have the airship robot recognize arrow marks, we used edge-based template matching. To control propeller units, we used PID and PD controller. The results of experiments demonstrated that the airship robot can move along the marks and can go up and down the stairs. It is shown the possibility that airship robot can become a robot which can move at wide range facilities.

Keywords: Template matching, moving robot, airship robot, PID control.

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302 Quick Similarity Measurement of Binary Images via Probabilistic Pixel Mapping

Authors: Adnan A. Y. Mustafa

Abstract:

In this paper we present a quick technique to measure the similarity between binary images. The technique is based on a probabilistic mapping approach and is fast because only a minute percentage of the image pixels need to be compared to measure the similarity, and not the whole image. We exploit the power of the Probabilistic Matching Model for Binary Images (PMMBI) to arrive at an estimate of the similarity. We show that the estimate is a good approximation of the actual value, and the quality of the estimate can be improved further with increased image mappings. Furthermore, the technique is image size invariant; the similarity between big images can be measured as fast as that for small images. Examples of trials conducted on real images are presented.

Keywords: Big images, binary images, similarity, matching.

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