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Ordination-fuzzy min-max neural network classifier on unlabelled pattern classification

Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence 2007年第2期20卷 173-179页

作者： Hu, Jing Yang, Jing Gao, Jun Laboratory of Image Information Processing School of Computer and Information Hefei University of Technology Hefei 230009 China Center for Biomimetic Sensing and Control Research Institute of Intelligent Machines Chinese Academy of Sciences Hefei 230031 China

An ordination-fuzzy min-max neural network (OFMM) based on non-metric multidimensional scaling (MDS) is proposed to solve the classification problems of unlabelled input pattern. Firstly, all the input patterns are sorted by MDS to get their similarity measures. Then these measures are used to supervise the following expansion and contraction stage of hyperboxes for classification. OFMM shows the improvements in the validity of unlabelled patterns classification, the network structure, and training time. The experimental results on standard dataset demonstrate that OFMM is a practical and effective classifier which is superior to the traditional general-fuzzy min -max neural network (GFMM).

关键词： Classifiers Fuzzy min-max neural network (FMMN) Multidimensional scaling (MDS) Similarity measures Unlabelled pattern

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Twin and scratch detection and removal in micrograph images of inconel™718

Twin and scratch detection and removal in micrograph images ...

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Machine Vision Applications in Industrial Inspection XIV

作者： Jakob, Gerhard Rinnhofer, Alfred Bischof, Horst Benesova, Wanda Joanneum Research Institute of Digital Image Processing Wastiangasse 6 8045 Graz Austria Technical University Graz Institute for Computer Graphics and Vision Inffeldgasse 16/II 8010 Graz Austria

ISBN: (纸本)0819461105

Grain size of forged nickel alloy is an important feature for the mechanical properties of the material. For fully automatic grain size evaluation in images of micrographs it is necessary to detect the boundaries of each grain. This grain boundary detection is influenced directly by artifacts like scratches and twins. Twins can be seen as parallel lines inside one grain, whereas a scratch can be identified as a sequence of collinear line segments that can be spread over the whole image. Both kinds of artifacts introduce artificial boundaries inside grains. To avoid wrong grain size evaluation, it is necessary to remove these artifacts prior to the size evaluation process. For the generation of boundary images various algorithms have been tested. The most stable results were achieved by grayscale reconstruction and a subsequent watershed segmentation. A modified line Hough transform with a third dimension in the Hough accumulator space, describing the distance of the parallel lines, is used to directly detect twins. Scratch detection is done by applying the standard line Hough transform followed by a rule based segment detection along the found Hough lines. The results of these operations give a detection rate of more than 90 percent for twins and more than 50 percent for scratches. © 2006 SPIE-IS&T.

关键词： Object recognition

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Capacity of steganographic channels

Capacity of steganographic channels

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7th Multimedia and Security Workshop 2005, MM and Sec'05

作者： Harmsen, Jeremiah J. Pearlman, William A. Center for Image Processing Research Electrical Computer and Systems Department Rensselaer Polytechnic Institute Troy NY

ISBN: (纸本)1595930329

An information-theoretic approach is used to determine the amount of information that may be safely transferred over a steganographic channel with a passive adversary. A steganographic channel, or stego-channel is a pair consisting of the channel transition probabilities and a detection function. When a message is sent, it first encounters a distortion (due to the channel), then is subject to inspection by a passive adversary (using the detection function). This paper presents results on the amount of information that may be transferred over an arbitrary stego-channel with vanishing probabilities of error and detection. Copyright 2005 ACM.

关键词： Channel capacity

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Harmonic-type Bézier surface over rectangular and triangular domain

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Journal of Information and Computational Science 2006年第2期3卷 325-332页

作者： Xu, Gang Wang, Guozhao Institute of Computer Graphics and Image Processing Department of Mathematics Zhejiang University Hangzhou 310027 China

In this paper, we present the modeling schemes of a class of Bézier surface with negative Gaussian curvature over the rectangular domain and the triangular domain. We have proved that the surface over the rectangular domain is fully determined by the control points of the two opposed boundary curves, and the surface over the triangular domain is fully determined by the control points on the first and second layers. In particular, we can control the shape of the surface by the shape parameter, which increases the degree of freedom of surface modeling.

关键词： computer graphics

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LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR CONTROL

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Asian Journal of Control 2008年第3期1卷

作者： Omid Shakernia Yi Ma T. John Koo Shankar Sastry Dept. of Electrical Engineering & Computer Science University of California at Berkeley Berkeley CA94720-1774 U.S.A. Tak-Kuen John Koo received the B.Eng. degree in 1992 in Electronic Engineering and the M.Phil. in 1994 in Information Engineering both from the Chinese University of Hong Kong. From 1994 to 1995 he was a graduate student in Signal and Image Processing Institute at the University of Southern California. He is currently a Ph.D. Candidate in Electrical Engineering and Computer Sciences at the University of California at Berkeley. His research interests include nonlinear control theory hybrid systems inertial navigation systems with applications to unmanned aerial vehicles. He received the Distinguished M.Phil. Thesis Award of the Faculty of Engineering The Chinese University of Hong Kong in 1994. He was a consultant of SRI International in 1998. Currently he is the team leader of the Berkeley AeRobot Team and a delegate of The Graduate Assembly University of California at Berkeley. He is a student member of IEEE and SIAM. S. Shankar Sastry received his Ph.D. degree in 1981 from the University of California Berkeley. He was on the faculty of MIT from 1980-82 and Harvard University as a Gordon McKay professor in 1994. He is currently a Professor of Electrical Engineering and Computer Sciences and Bioengineering and Director of the Electronics Research Laboratory at Berkeley. He has held visiting appointments at the Australian National University Canberra the University of Rome Scuola Normale and University of Pisa the CNRS laboratory LAAS in Toulouse (poste rouge) and as a Vinton Hayes Visiting fellow at the Center for Intelligent Control Systems at MIT. His areas of research are nonlinear and adaptive control robotic telesurgery control of hybrid systems and biological motor control. He is a coauthor (with M. Bodson) of “Adaptive Control: Stability Convergence and Robustness Prentice Hall 1989.” and (with R. Murray and Z. Li) of “A Mathematical Introduction to Robotic Manipulati

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.

关键词： Motion estimation computer vision based control unmanned air vehicle differential flatness

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Video object tracking based on a chamfer distance transform

Video object tracking based on a chamfer distance transform

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14th IEEE International Conference on image processing, ICIP 2007

作者： Zezhi, Chen Husz, Zsolt L. Wallace, Iain Wallace, Andrew M. Joint Research Institute in Signal and Image Processing School of Mathematics and Computer Science Heriot-Watt University Edinburgh EH14 4AS United Kingdom Joint Research Institute in Signal and Image Processing School of Engineering and Physical Sciences Heriot-Watt University Edinburgh EH14 4AS United Kingdom

ISBN: (纸本)1424414377

This paper describes the use of variable kernels based on the normalized Chamfer distance transform (NCDT) for mean shift, object tracking in colour video sequences. This replaces the more usual Epanechnikov kernel, improving target representation and localization without increasing the processing time, minimising the distance between successive frame RGB distributions using the Bhattacharya coefficient. The target shape which defines the NCDT is found either by regional segmentation or background-difference imaging, dependent on the nature of the video sequence. The improved performance is demonstrated on a number of colour video sequences. ©2007 IEEE.

关键词： image segmentation

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Single landmark based self-localization of mobile robots

Single landmark based self-localization of mobile robots

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3rd Canadian Conference on computer and Robot Vision, CRV 2006

作者： Bais, Abdul Sablatnig, Robert Gu, Jason Institute of Computer Technology Vienna University of Technology Vienna Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology Vienna Austria Robotics Research Group Department of Electrical and Computer Engineering Dalhousie University Halifax Canada

ISBN: (纸本)0769525423

In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allowed to modify the environment with special navigational aids. These features are sparse in our application domain and are frequently occluded by other robots. This makes simultaneous acquisition of two or more landmarks difficult. Therefore, we propose a system that requires a single landmark feature. The algorithm is based on range measurement of a single landmark from two arbitrary points whose displacement can be measured using dead-reckoning sensors. Range estimation is done with a stereo vision system. Simulation results show that the robot can localize itself if it can estimates range of the same landmark from two different position and if the displacement between the two position is known. © 2006 IEEE.

关键词： Mobile robots

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3D and Infrared Face Reconstruction from RGB data using Canonical Correlation Analysis

3D and Infrared Face Reconstruction from RGB data using Cano...

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International Conference on Pattern Recognition

作者： M. Reiter R. Donner G. Langs H. Bischof Pattern Recognition and Image Processing Group Vienna University of Technology Austria Graz University of Technology Institute for Computer Graphics and Vision Austria

In this paper, we apply a multiple regression method based on canonical correlation analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the correlation between two high dimensional signals. We first use CCA to perform 3D face reconstruction and in a separate application we predict near-infrared (NIR) face texture. In both cases, the input data are color (RGB) face images. Experiments show, that due to the correlation between input and output signal, only a small number of canonical factors are needed to describe the functional relation of RGB images to the respective output (NIR images and 3D depth maps) with reasonable accuracy

关键词： Shape Face detection Lighting image reconstruction image analysis image databases Pattern analysis Rendering (computer graphics) image color analysis Pattern recognition

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SPIHT algorithms using Depth First Search Algorithm with minimum memory usage

SPIHT algorithms using Depth First Search Algorithm with min...

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Annual Conference on Information Sciences and Systems (CISS)

作者： Mustafa Sakalli William A. Pearlman Masoud Farshchian Center for Image Processing Research ECSE Rensselaer Polytechnic Institute USA Center for Image Processing Research Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

This paper presents SPIHT and block-wise SPIHT algorithms where full depth first search algorithm is used to agglomerate significant bits at each bitplane. Search strategies used for SPIHT to date are more or less based on a breadth first search algorithm. The aim of this work is to minimize the final memory usage without paying additional overhead cost. DFS also brings benefits such as resolution scalability and a random access decodable bitstream.

关键词： Frequency Partitioning algorithms Costs Scalability Decoding Encoding Bit rate Multimedia communication Wavelet coefficients

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Using context and a genetic algorithm for knowledge-assisted image analysis

Using context and a genetic algorithm for knowledge-assisted...

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1st International Conference on Semantic and Digital Media Technologies, SAMT 2006

作者： Dasiopoulou, Stamatia Papadopoulos, George Th. Mylonas, Phivos Avrtihis, Yannis Kompatsiaris, Ioannis Information Processing Laboratory Electrical and Computer Engineering Department Aristotle University Thessaloniki Greece Informatics and Telematics Institute Centre for Research and Technology Greece Image Video and Multimedia Laboratory School of Electrical and Computer Engineering National Technical University Athens Greece

In this poster, we present an approach to contex-tualized semantic image annotation as an optimization problem. Ontologies are used to capture general and contextual knowledge of the domain considered, and a genetic algorithm is applied to realize the final annotation. Experiments with images from the beach vacation domain demonstrate the performance of the proposed approach and illustrate the added value of utilizing contextual information.

关键词： Ontology

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