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Texture defect detection using invariant textural features 23rd

引用

23rd German Association for pattern recognition Symposium, DAGM 2001

作者： Schael, Marc Institute for Pattern Recognition and Image Processing Computer Science Department Albert-Ludwigs-Universität Freiburg Germany

ISBN: (纸本)3540425969

In this paper we propose a novel method for the construction of invariant textural features for grey scale images. The textural features are based on an averaging over the 2D Euclidean transformation group with relational kernels. They are invariant against 2D Euclidean motion and strictly increasing grey scale transformations. Beside other fields of texture analysis applications we consider texture defect detection here. We provide a systematic method how to apply these grey scale features to this task. This will include the localization and classification of the defects. First experiments with real textile texture images taken from the TILDA database show promising results. They are presented in this paper. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Defects

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Efficient 3D vertex detection in range images acquired with a laser sensor 23rd

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23rd German Association for pattern recognition Symposium, DAGM 2001

作者： Katsoulas, Dimitrios Bergen, Lothar Institute for Pattern Recognition and Image Processing Computer Science Department Albert-Ludwigs-Universität Freiburg Germany

ISBN: (纸本)3540425969

In many branches of industry, piled box-like objects have to be recognized, grasped and transferred. Unfortunately, existing systems only deal with the most simple configurations (i.e. neatly placed boxes) effectively. It is known that the detection of 3D-vertices is a crucial step towards the solution of the problem, since they reveal essential information about the location of the boxes in space. In this paper we present a technique based on edge detection and robust line fitting, which efficiently detects 3D-vertices. Combining this technique with the advantages of a time of flight laser sensor for data acquisition, we obtain a fast system which can operate in adverse environments independently of lighting conditions. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Edge detection

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SIMBA – Search images by appearance

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23rd German Association for pattern recognition Symposium, DAGM 2001

作者： Siggelkow, Sven Schael, Marc Burkhardt, Hans Institute for Pattern Recognition and Image Processing Computer Science Department Albert-Ludwigs-Universität Freiburg Germany

ISBN: (纸本)3540425969

In this paper we present SIMBA, a content based image retrieval system performing queries based on image appearance. We consider absolute object positions irrelevant for image similarity here and therefore propose to use invariant features. Based on a general construction method (integration over the transformation group), we derive invariant feature histograms that catch different cues of image content: features that are strongly influenced by color and textural features that are robust to illumination changes. By a weighted combination of these features the user can adapt the similarity measure according to his needs, thus improving the retrieval results considerably. The feature extraction does not require any manual interaction, so that it might be used for fully automatic annotation in heavily fluctuating image databases. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Search engines

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Reconstruction of specular surfaces using polarization imaging

Reconstruction of specular surfaces using polarization imagi...

引用

Conference on computer Vision and pattern recognition (CVPR)

作者： S. Rahmann N. Canterakis Institute for Pattern Recognition and Image Processing Computer Science Department University of Freiburg Freiburg im Breisgau Germany

ISBN: (纸本)0769512720

Traditional intensity imaging does not offer a general approach for the perception of textureless and specular reflecting surfaces. Intensity based methods for shape reconstruction of specular surfaces rely on virtual (i.e. mirrored) features moving over the surface under viewer motion. We present a novel method based on polarization imaging for shape recovery of specular surfaces. This method overcomes the limitations of the intensity based approach because no virtual features are required. It recovers whole surface patches and not only single curves on the surface. The presented solution is general as it is independent of the illumination. The polarization image encodes the projection of the surface normals onto the image and therefore provides constraints on the surface geometry. Taking polarization images from multiple views produces enough constraints to infer the complete surface shape. The reconstruction problem is solved by an optimization scheme where the surface geometry is modelled by a set of hierarchical basis functions. The optimization algorithm proves to be well converging, accurate and noise resistant. The work is substantiated by experiments on synthetic and real data.

关键词： image reconstruction Surface reconstruction Polarization Shape Geometry Surface texture Lighting Solid modeling image converters Multi-stage noise shaping

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Illumination insensitive eigenspaces

Illumination insensitive eigenspaces

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International Conference on computer Vision (ICCV)

作者： H. Bischof H. Wildenauer A. Leonardis Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia

ISBN: (纸本)0769511430

Variations in illumination can have a dramatic effect on the appearance of an object in an image. In this paper we propose how to deal with illumination variations in eigenspace methods. We demonstrate that the eigenimages obtained by a training set under a single illumination condition (ambient light) can be used for recognition of objects taken under different illumination conditions. The major idea is to incorporate a set of gradient based filter banks into the eigenspace recognition framework. This can be achieved since the eigenimage coefficients are invariant for linearly filtered images (input and eigenimages). To achieve further illumination insensitivity we devised a robust procedure for coefficient recovery. The proposed approach has been extensively evaluated on a set of 2160 images and the results were compared to other approaches.

关键词： Lighting Nonlinear filters Principal component analysis image coding Object recognition Filtering Filter bank image recognition Information science image sampling

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An efficient depalletizing system based on 2D range imagery

An efficient depalletizing system based on 2D range imagery

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IEEE International Conference on Robotics and Automation (ICRA)

作者： D.K. Katsoulas D.I. Kosmopoulos Institute for Pattern Recognition and Image Processing University of Freiburg Freiburg im Breisgau Germany Department of electrical engineering division of Computer Science National and Technical University of Athens Athens Greece

ISBN: (纸本)0780365763

We propose an efficient approach towards the solution of the de-palletizing problem, based on active vision. We describe a system comprising an industrial robot and a time of flight laser sensor, which performs the depalletizing task in real time, and independently of lighting conditions. In our case, the target objects are solid boxes of known identical dimensions, neatly layered but with arbitrary orientation within a layer, which are all placed on a platform. The layered structure of the target platform allows for 2D imagery. The system locates the position of the boxes by tracking one of the corners they expose to the laser source. The system locates the desired corners by applying the scan line approximation technique, adapted to fit the needs of our application, to the 2D input data. The advantages of our system over existing applications are its simplicity, robustness, speed and ease of installation.

关键词： Robustness Service robots Humans pattern recognition image processing computer science Robot sensing systems Sensor phenomena and characterization Solids Target tracking

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Handwritten Chinese character segmentation using a two-stage approach

Handwritten Chinese character segmentation using a two-stage...

引用

International Conference on Document Analysis and recognition

作者： Shuyan Zhao Zheru Chi Pengfei Shi Qing Wang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Centre for Multimedia Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China Department of Computer Science and Engineering Northwestern Polytechnical University Xi'an China

ISBN: (纸本)0769512631

Correct segmentation of handwritten Chinese characters is crucial to the successful recognition. However, because of the many difficulties involved, little work has been done in this area. In this paper, a two-stage approach is addressed to segment unconstrained handwritten Chinese character strings. A string is first coarsely segmented according to the background skeleton and vertical projection after a proper image preprocessing. At the fine segmentation stage that follows, the strokes that may contain segmentation points are first identified. The feature points are then extracted from candidate strokes and taken as segmentation point candidates through each of which a segmentation path may be formed. Geometric features are extracted and fuzzy decision rules learned from examples are used to evaluate the segmentation paths. By using this two-stage segmentation approach, we can achieve both good performance and efficiency in segmenting unconstrained handwritten Chinese characters.

关键词： image segmentation Character recognition pattern recognition Handwriting recognition Signal processing image processing computer science Electronic mail image recognition Skeleton

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Grouping edge points into line segments by sequential hough transformation

Grouping edge points into line segments by sequential hough ...

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15th International Conference on pattern recognition, ICPR 2000

作者： Zhang, Xiaofeng Burkhardt, Hans Pattern Recognition and Image Processing Dept. of Computer Science University of Freiburg Freiburg79110 Germany

ISBN: (纸本)0769507506

An algorithm to group edge points into digital line segments with Hough transformation is described in this paper. The edge points are mapped onto the parameter domain dis-cretked at specific intervals, on which peaks appear to represent different line segments. By modeling each peak as a Gaussian function in the parameter domain, a region, to which the edge points are supposed to be mapped, is determined. Then the edge points are grouped and the parameters for a line segment are computed. For the edges including multiple line segments, a sequential Hough transformation, detecting peaks one by one in the parameter domain, is implemented and the points from the region around each peak are grouped, thus the line segments are described. Experiments show the robustness of the algorithm implemented on both generated edges disturbed by different noise levels and real images taken from indoor environment. © 2000 IEEE.

关键词： Edge detection

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Invariant grey-scale features for 3D sensor-data

Invariant grey-scale features for 3D sensor-data

引用

International Conference on pattern recognition

作者： M. Schael S. Siggelkow Institute for Pattern Recognition and Image Processing Computer Science Department University of Freiburg Freiberg Germany

ISBN: (纸本)0769507506

A technique for the construction of invariant features of 3D sensor-data is proposed. Invariant grey-scale features are characteristics of grey-scale sensor-data which remain constant if the sensor-data is transformed according to the action of a transformation group. The proposed features are capable of recognizing 3D objects independent of their orientation and position, which can be used e.g. in medical image analysis. The computation of the proposed invariants needs no preprocessing like filtering, segmentation, or registration. After the introduction of the general theory for the construction of invariant features for 3D sensor-data, the paper focuses on the special case of 3D Euclidean motion which is typical for rigid 3D objects. Due to the fact that we use the function of local support the calculated invariants are also robust with respect to independent Euclidean motion, articulated objects, and even topological deformations. The complexity of the method is linear in the data-set size which may be too high for large 3D objects. Therefore approaches for the acceleration of the computation are given. First experimental results for artificial 3D objects are presented in the paper to demonstrate the invariant properties of the proposed features.

关键词： Geometry pattern recognition Biomedical imaging Robustness image processing computer science image recognition image motion analysis Lubricating oils image segmentation

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Grouping edge points into line segments by sequential Hough transformation

Grouping edge points into line segments by sequential Hough ...

引用

International Conference on pattern recognition

作者： Xiaofeng Zhang H. Burkhardt Chair of Pattern Recognition and Image Processing Department of Computer Science University of Freiburg Freiburg im Breisgau Germany

ISBN: (纸本)0769507506

An algorithm to group edge points into digital line segments with Hough transformation is described. The edge points are mapped onto the parameter domain discretized at specific intervals, on which peaks appear to represent different line segments. By modeling each peak as a Gaussian function in the parameter domain, a region to which the edge points are supposed to be mapped is determined. Then the edge points are grouped and the parameters for a line segment are computed. For the edges including multiple line segments, a sequential Hough transformation for detecting peaks one by one in the parameter domain is implemented, and the points from the region around each peak are grouped, thus the line segments are described. Experiments show the robustness of the algorithm implemented on both the generated edges disturbed by different noise levels and real images taken from an indoor environment.

关键词： image segmentation image edge detection Indoor environments Face detection pattern recognition image processing computer science Noise robustness Noise level Noise measurement

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