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Pixel classification by divergence-based integration of multiple texture methods and its application to fabric defect detection

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25th Symposium of the German Association for Pattern Recognition, DAGM 2003

作者： Garcia, Miguel Angel Puig, Doménec Intelligent Robotics and Computer Vision Group Department of Computer Science and Mathematics Rovira i Virgili University Av. Països Catalans 26 Tarragona43007 Spain

ISBN: (纸本)3540408614

This paper presents and evaluates a pixel-based texture classifier that integrates multiple texture feature extraction methods through a new scheme based on the Kullback J-divergence. Experimental results show that the proposed technique yields qualitatively better image segmentations than well-known both supervised and unsupervised texture classifiers based on specific families of texture methods. A practical application to fabric defect detection is presented. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Image segmentation

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Calibration of A Structured Light-Based Stereo Catadioptric Sensor

Calibration of A Structured Light-Based Stereo Catadioptric ...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Radu Orghidan Joaquim Salvi El Mustapha Mouaddib Computer Vision and Robotics Group Institute of Informatics and Applications Girona Catalonia Spain

Catadioptric sensors are combinations of mirrors and lenses made in order to obtain a wide field of view. In this paper we propose a new sensor that has omnidirectional viewing ability and it also provides depth information about the nearby surrounding. The sensor is based on a conventional camera coupled with a laser emitter and two hyperbolic mirrors. Mathematical formulation and precise specifications of the intrinsic and extrinsic parameters of the sensor are discussed. Our approach overcomes limitations of the existing omni-directional sensors and eventually leads to reduced costs of production.

关键词： Mirrors Cameras Mathematical model Robot sensing systems Equations Laser modes Lasers

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Towards a real-time vision-based navigation system for a small-class UUV

Towards a real-time vision-based navigation system for a sma...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： R. Garcia T. Nicosevici P. Ridao D. Ribas Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory.

关键词： Real time systems Motion estimation Underwater vehicles Sea measurements Position measurement Dead reckoning Sonar navigation Robot vision systems Hydrodynamics Costs

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Active regions for colour texture segmentation integrating region and boundary information

Active regions for colour texture segmentation integrating r...

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IEEE International Conference on Image Processing

作者： X. Munoz J. Freixenet X. Cufi J. Marti Computer Vision and Robotics Group. Institute of Informatics and Applications University of Girona Girona Spain

In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method.

关键词： Image segmentation Proposals Data mining Image edge detection Pixel computer vision Robot vision systems Informatics Application software Kernel

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Pixel classification through divergence-based integration of texture methods with conflict resolution

Pixel classification through divergence-based integration of...

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IEEE International Conference on Image Processing

作者： D. Puig M.A. Garcia Intelligent Robotics and Computer Vision Group Department of Computer Science and Mathematics Rovira i Virgili University Tarragona Spain

This paper presents a new technique for combining multiple texture feature extraction methods in order to classify the pixels of an input image into a set of texture models of interest. The problem of integrating multiple texture methods for classification purposes is cast as a collaborative decision making problem. Each texture method is considered to be an expert that gives an opinion about the membership of every input image pixel to each texture model, along with a conviction about that judgement. A conviction measure based on the Kullback J-divergence between texture models is proposed, along with an arbitration mechanism that combines those convictions by taking into account conflicts that may occur when different experts disagree with a similar strength. The proposed technique is compared to previous pixel-based texture classifiers by using real textured images.

关键词： Pixel Intelligent robots Feature extraction Collaboration Decision making Robot vision systems computer vision computer science Mathematics Soil

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ROV-Aided Dam Inspection: Practical Results

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IFAC Proceedings Volumes 2003年第21期36卷 271-274页

作者： Joan Batlle Tudor Nicosevici Rafael Garcia Marc Carreras Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona E.P.S. 17071 Girona Spain

Nowadays Unmanned Underwater Vehicles (UUVs) are used in a growing number of underwater missions, mostly inspections of different types of installations such as: telecommunication cables, pipes or oil extraction installations. A field where UUVs are still starting to prove their utility is dam inspection. This paper presents details our first approach in dam inspection. A set of experiments carried out at a dam in Romania is described. Advantages and drawbacks of using a small-class underwater vehicle are analyzed for this type of missions.

关键词： computer vision teleoperation fault detection motion estimation

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Classification of textures seen from different distances and under varying illumination direction

Classification of textures seen from different distances and...

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IEEE International Conference on Image Processing

作者： X. Llado J. Marti M. Petrou Computer Vision and Robotics Group University of Girona Girona Spain Informatics and Telematic Institute EKETA Thessaloniki Greece

Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations produce displacements of class members in the feature space, increasing the failure rates of texture classifiers. To avoid this problem, a model-based texture recognition system which classifies textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source colour photometric stereo, used to generate 2D image textures under different illumination directions. The recognition system combines coocurrence matrices for feature extraction with a Nearest Neighbour classifier. Moreover, the recognition allows one to guess the approximate direction of the illumination used to capture the test image.

关键词： Lighting Surface texture Image texture Photometry Cameras Informatics computer vision Robot vision systems Application software Stereo vision

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Set-permutation-occurrence matrix based texture segmentation

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1st Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2003

作者： Zwiggelaar, Reyer Blot, Lilian Raba, David Denton, Erika R. E. School of Information Systems University of East Anglia Norwich United Kingdom Computer Vision and Robotics Group University of Girona Girona Spain Department of Breast Imaging Norfolk and Norwich University Hospital Norwich United Kingdom

ISBN: (纸本)3540402179

We have investigated a combination of statistical modelling and expectation maximisation for a texture based approach to the segmentation of mammographic images. Texture modelling is based on the implicit incorporation of spatial information through the introduction of a set-permutation-occurrence matrix. Statistical modelling is used for data generalisation and noise removal purposes. Expectation maximisation modelling of the spatial information in combination with the statistical modelling is evaluated. The developed segmentation results are used for automatic mammographic risk assessment. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Risk assessment

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Calibration of A Structured Light-Based Stereo Catadioptric Sensor

Calibration of A Structured Light-Based Stereo Catadioptric ...

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Conference on computer vision and Pattern Recognition Workshop, CVPRW 2003

作者： Orghidan, Radu Salvi, Joaquim Mouaddib, El Mustapha Computer Vision and Robotics Group Institute of Informatics and Applications Universitat de Girona Avda. Lluis Santalo s/n GironaCatalonia17071 Spain Centre de Robotique Electrotechnique et d'Automatique Université de Picardie Jules Verne Rue du Moulin Neuf Amiens80000 France

ISBN: (纸本)0769519008

关键词： Stereo vision

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Non-Destructive Disassembly Robot Cell for Demanufacturing Automation

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IFAC Proceedings Volumes 2003年第23期36卷 97-102页

作者： S.T. Puente F. Torres R. Aracil Automatics Robotics and Computer Vision Group (http://www.disc.ua.es/aurova) Dept. of Physics Systems Engineering and Signal Theory. University of Alicante (Spain) DISAM Polytechnic University of Madrid (Spain)

Product disassembly for reusing or recycling can be done in a destructive or not-destructive way. Furthermore, to achieve an automatic disassembly, a robot arm has to be considered for doing the desired task. This paper presents the structure of a flexible automatic-demanufacturing system which includes a robot arm for the disassembly tasks. This paper makes special emphasis on how the fusion of the information from the sequence planner with the information from the movement generator can be used to take a robot arm into consideration, which accomplishes the disassembly tasks. Finally, the automatic disassembly concepts are used for the disassembly of a laptop PC.

关键词： disassembly non-destructive disassembly demanufacturing automation robotics data fusion

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