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Object Based Clustering Using Hybrid Algorithms

Object Based Clustering Using Hybrid Algorithms

引用

International conference on computer graphics, imaging and Visualization, CGIV

作者： Nor Hafizah Abd. Razak Noridayu Manshor Mandava Rajeswari Dhanesh Ramachandram Computer Vision Research Group Universiti Sains Islam Malaysia Malaysia

ISBN: (纸本)9780769533599;0769533590

This paper presents a hybrid algorithm for object based clustering. The algorithm is designed based on hybrid of hierarchical and k-means clustering algorithm. For this work, we used dataset consist of natural imagery collected from PASCAL database 2006 collection and Google images. A collection of low level features image is used to validate the performance of our approach. Experimental results show that hybrid algorithm produced higher accuracy compared to k-means and hierarchical algorithm by up to 25%.

关键词： Clustering algorithms Shape Feature extraction Classification algorithms Partitioning algorithms Algorithm design and analysis Accuracy

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Textured Renyi Entropy for Image Thresholding

Textured Renyi Entropy for Image Thresholding

引用

International conference on computer graphics, imaging and Visualization, CGIV

作者： Ahmad Adel Abu Shareha Mandava Rajeswari Dhanesh Ramachandram Universiti Sains Malaysia Minden Pulau Pinang MY School of Computer Science Universiti Sains Islam Malaysia Malaysia School of Computer Science Universiti Sains Malaysia

ISBN: (纸本)9780769533599;0769533590

This paper introduces Textured Renyi Entropy for image thresholding based on a novel combination mechanism. The Renyi Entropy is extended by modifying its priori, while still preserving overall functionality. An optional priori is introduced to improve accuracy. The priori modification allows adding of texture information in an efficient way, which results in more accurate thresholding. Furthermore, the proposed mechanism allows adding other features after some normalization. Finally the novel way allows adding multiple features simultaneously using the modified priors.

关键词： Entropy Pixel Mathematical model Equations Histograms Correlation Image segmentation

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An Animated Cryptographic Learning Object

An Animated Cryptographic Learning Object

引用

International conference on computer graphics, imaging and Visualization, CGIV

作者： Rachid Anane Kevin Purohit Georgios Theodoropoulos School of Computer Science University of Binningham UK Department of Computer Science Coventry University UK

ISBN: (纸本)9780769533599

Algorithmic animation has been the focus of intense research in many disciplines and its impact on the educational process has been marked by increasing learner autonomy. Research in this field is driven by the belief that algorithm animation can be a more effective means of instruction than manual or verbal modes of delivery. Encryption algorithms in particular offer an interesting domain for the application of animation principles in learner/content interaction. The main challenge however has been how to design effective animations with a pedagogical value. This paper is concerned with the presentation of an animation of the DES algorithm that exhibits many of the features of useful instructional material. Its pedagogical value is expressed in terms of intrinsic qualities and, in particular, the degree of interactivity and the granularity of abstraction.

关键词： Animation Cryptography Algorithm design and analysis Heuristic algorithms Schedules Complexity theory Tutorials

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Visualization of Hybrid, N-Body and Octree-Based Adaptive Mesh Resolution Parallelized Simulations

Visualization of Hybrid, N-Body and Octree-Based Adaptive Me...

引用

International conference on computer graphics, imaging and Visualization, CGIV

作者： D. Pomarède Y. Fidaali R. Teyssier CEA Saclay Institut de Recherche sur les Lois Fondamentales de l''Univers DSM IRFU SEDI LILAS and SAp Gif-sur-Yvette France

ISBN: (纸本)9780769533599;0769533590

In this paper, we report on the development of a visualization software which address the issue of the interactive visualization of three-dimensional hybrid simulations combining an N-body module and a grid-based solver with an octree-based adaptive mesh. The difficulty inherent to the hybrid nature of the data and the complexity of the mesh structure used to describe both scalar and vector fields is enhanced by the fact that simulations are parallelized. Large-scale simulations are conducted on high-performance mainframes with potentially thousands of processors associated with a non-trivial domain decomposition. The software we present is deployed in the framework of IDL object graphics as part of the SDvision graphics tool used primarily in the visualization of astrophysical simulations. It combines in a single scene the graphics objects of the N-body system and the grid-based fields, together with a visual representation of the octree mesh, suitable for interactive and immersive navigation.

关键词： Data visualization graphics Adaptation model Visualization Software Computational modeling Image color analysis

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Skew Estimation and Correction of Text Using Bounding Box

Skew Estimation and Correction of Text Using Bounding Box

引用

International conference on computer graphics, imaging and Visualization, CGIV

作者： Muhammad Sarfraz Zeehasham Rasheed Department of Information and Computer Science King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Information Science Kuwait University Safat Kuwait

ISBN: (纸本)9780769533599;0769533590

This paper, in addition to reporting some existing techniques, proposes a new technique for skew correction. It includes a novel document skew detection algorithm based on bounding box technique. The algorithm works quite efficiently for detecting the skew and then correcting it. The method has been experimented on various text documents and very promising results have been achieved given more than 97% accuracy. A comparative study has been reported to provide a detailed analysis of the proposed method together with some other existing methods in the literature.

关键词： Algorithm design and analysis Principal component analysis Pixel Estimation Mathematical model Equations Optical character recognition software

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Normalized Cross-Correlation Based Fingerprint Matching

Normalized Cross-Correlation Based Fingerprint Matching

引用

International conference on computer graphics, imaging and Visualization, CGIV

作者： Deepak Kumar Karna Suneeta Agarwal Shankar Nikam Computer Science Department Motilal Nehru National Institute of Technology Allahabad India Computer Science Department Motilal Nehru National Institute of Technology Allahabad

ISBN: (纸本)9780769533599;0769533590

To perform fingerprint matching based on the number of corresponding minutia pairings, has been in use for quite sometime. But this technique is not very efficient for recognizing the low quality fingerprints. To overcome this problem, some researchers suggest the correlation technique which provides better result. Use of correlation-based methods is increasing day-by-day in the field of biometrics as it provides better results. In this paper, we propose normalized cross-correlation technique for fingerprint matching to minimize error rate as well as reduce the computational effort than the minutiae matching method. The EER (equal error rate) obtained from result till now with minutiae matching method is 3%, while that obtained for the method proposed in this paper is approx 2% for all types of fingerprints in combined form.

关键词： Fingerprint recognition Image matching Correlation Testing Fingers Pixel Degradation

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Overlaid Text Recognition for Matching Soccer-Concept Keywords

Overlaid Text Recognition for Matching Soccer-Concept Keywor...

引用

International conference on computer graphics, imaging and Visualization, CGIV

作者： Alfian Abdul Halin Mandava Rajeswari Dhanesh Ramachandram School of Computer Sciences Universiti Sains Islam Malaysia Malaysia School of Computer Sciences Universiti Sains Malaysia

ISBN: (纸本)9780769533599;0769533590

Overlaid-text appears frequently in broadcast sports video. They provide a plethora of information regarding the goings-on of a particular game. Examples include important events and video segments of interest such as bookings and half-time analysis, respectively. Furthermore, it is common that overlaid text is displayed when a particular concept is happening or has happened. This paper presents a concept identification framework, based on matched keywords from overlaid-text extraction and recognition. Possible occurrences of overlaid-text in soccer programs are extracted and recognized, and then matched against a soccer-term database. Preliminary experiments show reliable character extraction, whose recognition has been successfully matched with keywords within the database.

关键词： Optical character recognition software Databases Character recognition Visualization Image edge detection Pixel Image color analysis

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A Real Time Simulation of Flood Hazard

A Real Time Simulation of Flood Hazard

引用

International conference on computer graphics, imaging and Visualization, CGIV

作者： Jasrul Nizam Ghazali Amirrudin Kamsin Faculty of Computer Science and Information Technology University Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9780769533599;0769533590

Kuala Lumpur city is located at the confluence of two rivers and are flood prone area. With rapid development and uncontrolled town planning, the city had experience several major flash flood incidents and have caused tremendous damage to country. This research describes a study made to model and simulate the flash flood incident that struck Kuala Lumpur on 10 June 2007 using 3D computer graphic and fluid simulation techniques. The aim is to examine the stability and effectiveness of this approach as a solution tool for environmental hazard studies. Particle-based method used to model the fluid objects using MAYA software. Light detection and ranging (LIDAR) data and remote sensing imagery were used to model the study area. The main contribution of this study is the introduction of this approach to enhance realistic visualization for environmental studies thus enable better planning and countermeasures created to prevent the disaster.

关键词： Computational modeling Floods Fluids Solid modeling Laser radar Rivers computer graphics

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Kohonen-Swarm Algorithm for Unstructured Data in Surface Reconstruction

Kohonen-Swarm Algorithm for Unstructured Data in Surface Rec...

引用

International conference on computer graphics, imaging and Visualization, CGIV

作者： Fadni Bin Forkan Siti Mariyam Hj Shamsuddin Faculty of Computer Science & Information Systems Universiti Teknologi Malaysia Skudai Johor Malaysia

ISBN: (纸本)9780769533599;0769533590

This work introduces a new method for surface reconstruction based on hybrid soft computing techniques: Kohonen network and particle swarm optimization (PSO). Kohonen network learns the sample data through mapping grid that can grow. The implementation is executed by generating Kohonen mapping framework of the data subsequent to the learning process. Consequently, the learned and well-represented data become the input for surface fitting procedure, and in this study, PSO is proposed to probe the optimum fitting points on the surfaces. The proposed algorithms are applied on different types of curve and surfaces to observe its ability in reconstructing the objects while preserving the original shapes. The experimental results have shown that the proposed algorithm have succeeded in producing the reconstructed surfaces with minimum errors generated.

关键词： Surface reconstruction Surface treatment Surface fitting Neurons Image reconstruction Fitting Algorithm design and analysis

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Object Class Recognition Using NEAT-Evolved Artificial Neural Network

Object Class Recognition Using NEAT-Evolved Artificial Neura...

引用

International conference on computer graphics, imaging and Visualization, CGIV

作者： Mozaherul Hoque Abul Hasanat Siti Zubaidah Harun Dhanesh Ramachandram Mandava Rajeswari Computer Vision Research Group School of Computer Sciences Universiti Sains Islam Malaysia Malaysia Computer Vision Research Group Universiti Sains Malaysia

ISBN: (纸本)9780769533599;0769533590

Object class recognition is a highly challenging area in computer vision and machine learning. In this paper, we introduce a novel approach to object class recognition using Neuro Evolution of Augmenting Topologies (NEAT) to evolve artificial neural networks (ANN) capable of taking advantage of the robust SIFT feature based descriptor histograms. We claim that NEAT can produce ANN classifier which exhibits outstanding ability of learning from only afew training examples without sacrificing accuracy. Our empirical evaluations against the performance of state of the art statistical machine learning method such as support vector machine show that NEAT-evolved ANN classifier outperforms by an average of 9.96% higher accuracy when presented with very small training set proving its superior ability to generalize its learning.

关键词： Artificial neural networks Visualization Classification algorithms Genetics Support vector machines Training Image recognition

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