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IEEE International Conference on image processing

作者： A. Licsar L. Czuni T. Sziranyi Department of Image Processing and Neurocomputing University of Veszprém Veszprem Hungary Analogical & Neural Computing Laboratory Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

We have developed a new semi-automatic neural network based method to detect blotches with low false alarm rate on archive films. Blotches can be modeled as temporal intensity discontinuities, hence false detection results originate from object motion (e.g. occlusion), non-rigid objects or erroneous motion estimation. In practice, usually, after the automatic detection step the false alarms are removed manually by an operator, significantly decreasing the efficiency of the restoration process. Our post-processing method classifies each detected blotch by its image features to minimize false results and the necessity of human intervention. The proposed method is tested on real archive sequences.

关键词： Object detection image restoration Motion detection Motion estimation Humans Neural networks Optical films Degradation Costs image motion analysis

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Creating animations combining stochastic paintbrush transformation and motion detection

Creating animations combining stochastic paintbrush transfor...

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International Conference on Pattern Recognition

作者： L. Kovacs T. Sziranyi Department of Image Processing and Neurocomputing University of Veszprém Hungary Analogical Computing Laboratory Computer & Automation Inst Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

In this paper we propose a method for creating animation and animation-like video sequences from any ordinary video recorded by any means available. The method is based on paintbrush transformation, developed and patented by our department, and on different motion detection algorithms. One of the goals of the method is to obtain animations, cartoon-like outputs from a usual camera-recorded image sequence. The method inherits properties of the paintbrush transformation method like well-defined contours, acceptable distortion, and a painting-like view with no fine details below a limit. The resulting output is a series of video frames stored as brush-strokes and motion data between the frames, compressed for size reduction. This output can be converted to any available video format by decompression, frame-reconstruction and recompression.

关键词： Animation Stochastic processes Motion detection Painting Video compression image coding image sequences image processing Laboratories Automation

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Hand gesture recognition in camera-projector system

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8th European Conference on Computer Vision, ECCV 2004 and International Workshop on Human-Computer Interaction, HCI 2004

作者： Licsár, Attila Szirányi, Tamás University of Veszprém Department of Image Processing and Neurocomputing Egyetem u. 10 VeszprémH-8200 Hungary Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Kendeu. 13-17 BudapestH-1111 Hungary

ISBN: (纸本)3540220127

Our paper proposes a vision-based hand gesture recognition system. It is implemented in a camera-projector system to achieve an augmented reality tool. In this configuration the main problem is that the hand surface reflects the projected background, thus we apply a robust hand segmentation method. Hand localizing is based on a background subtraction method, which adapts to the changes of the projected background. Hand poses are described by a method based on modified Fourier descriptors, which involves distance metric for the nearest neighbor classification. The proposed classification method is compared to other feature extraction methods. We also conducted tests on several users. Finally, the recognition efficiency is improved by the recognition probabilities of the consecutive detected gestures by maximum likelihood approach. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Augmented reality

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Anisotropic diffusion as a preprocessing step for efficient image compression

Anisotropic diffusion as a preprocessing step for efficient ...

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International Conference on Pattern Recognition

作者： T. Sziranyi I. Kopilovic B.P. Toth Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences Budapest Hungary Department of Image Processing & Neurocomputing University of Veszprem Veszprem Hungary

Anisotropic diffusion is an image enhancement method. It is a nonlinear process which removes noise and irrelevant details while preserving the edges, i.e. it "extracts" the essential visual information. The paper proposes a useful application of anisotropic diffusion in image data compression. We argue that for high compression an anisotropic diffusion preprocessing results in better quality of the decoded image.

关键词： Anisotropic magnetoresistance image coding image processing Transform coding Space heating Equations Laboratories Automation Time of arrival estimation Data mining

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Anisotropic diffusion as a preprocessing step for efficient image compression

Anisotropic diffusion as a preprocessing step for efficient ...

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14th International Conference on Pattern Recognition, ICPR 1998

作者： Sziranyi, Tamás Kopilovic, Ivan Toth, Barnabas P. University of Veszprem Department of Image Processing and Neurocomputing Egyetem u. 10 H-8200 Veszprem Hungary Analogical and Neural Computing Laboratory Comp. and Automation Inst. Hungarian Academy of Sciences Kende u. 13-17 H-1111 Budapest Hungary

ISBN: (纸本)0818685123

关键词： image enhancement

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Object Oriented Motion-Segmentation for Video-Compression in the CNN-UM

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Journal of VLSI signal processing systems for signal, image and video technology 1999年第2期23卷 479-496页

作者： Szirányi, Tamás László, Károly Czúni, László Ziliani, Francesco Analogical and Neural Computing Laboratory Comp. & Automation Inst. Hungarian Academy of Sciences Budapest Hungary Department of Image Processing and Neurocomputing University of Veszprém Veszprém Hungary Signal Processing Laboratory Swiss Federal Institute of Technology Lausanne Switzerland

Object-oriented motion segmentation is a basic step of the effective coding of image-series. Following the MPEG-4 standard we should define such objects. In this paper, a fully parallel and locally connected computation model is described for segmenting frames of image sequences based on spatial and motion information. The first type of the algorithm is called early segmentation. It is based on spatial information only and aims at providing an over-segmentation of the frame in real-time. Even if the obtained results do not minimize the number of regions, it is a good starting point for higher level post processing, when the decision on how to regroup regions in object can rely on both spatial and temporal information. In the second type of the algorithm stochastic optimization methods are used to form homogenous dense optical vector fields which act directly on motion vectors instead of 2D or 3D motion parameters. This makes the algorithm simple and less time consuming than many other relaxation methods. Then we apply morphological operators to handle disocclusion effects and to map the motion field to the spatial content. Computer simulations of the CNN architecture demonstrate the usefulness of our methods. All solutions in our approach suggest a fully parallel implementation in a newly developed CNN-UM VLSI chip architecture.

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Random paintbrush transformation

Random paintbrush transformation

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International Conference on Pattern Recognition

作者： T. Sziranyi Z. Toth Analogical computing Laboratory Computer & Automation Inst Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Department of Image Processing and Neurocomputing University of Veszprém Veszprem Hungary

ISBN: (纸本)0769507506

A paintbrush-like image transformation is proposed. It is based on a random searching to insert brush-strokes into a generated image at decreasing scale of brush-sizes, without predefined models or interaction. One of the goals of the method is to transform the image into a representation that is very similar to the human sensation of artistic images. We introduce a sequential multiscale image decomposition method, based on simulated rectangular-shaped paintbrush strokes. The resulting images look like good-quality paintings with well-defined contours, at an acceptable distortion compared to the original image. The image can be described with the parameters of the consecutive paintbrush strokes, resulting in a parameter-series that can be used for compression. The painting process can be used for scale-space image representation, segmentation and contour detection, and image representation for retrieval purposes.

关键词： Painting Humans image coding Layout image representation Fractals Laboratories Automation image generation image decomposition

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Creating animations combining stochastic Paintbrush Transformation and motion detection

Creating animations combining stochastic Paintbrush Transfor...

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作者： Kovács, Levente Szirányi, Tamás University of Veszprém Department of Image Processing and Neurocomputing Egyetem u. 10 H-8200 Veszprém Hungary Analogical Computing Laboratory Comp. and Automation Inst. Hungarian Academy of Sci. Kende u. 13-17 H-1111 Budapest Hungary

In this paper we propose a method for creating animation and animation-like video sequences from about any ordinary video recorded by any means available. The method is based on the Paintbrush Transformation earlier invented, developed and patented by our department [7], and on different motion detection algorithms [3,4,5]. One of the goals of the method is to obtain animations, cartoon-like outputs from a usual camera-recorded image sequence. The method inherits the properties of the paintbrush transformation method like well-defined contours, acceptable distortion, a painting-like view with no fine details below a limit. The resulting output is a series of video frames stored as brush-strokes and motion data between the frames, compressed for size reduction. This output can be converted to any available video format by decompression, frame-reconstruction and recompression. © 2002 IEEE.

关键词： Animation

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Supervised training based hand gesture recognition system

Supervised training based hand gesture recognition system

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作者： Licsár, Attila Szirányi, Tamás University of Veszprém Department of Image Processing and Neurocomputing Egyetem u. 10 H-8200 Veszprém Hungary Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Kende u. 13-17 H-1111 Budapest Hungary

We have developed a hand gesture recognition system, based on the shape analysis of static gestures, for Human Computer Interaction purposes. Our appearance-based recognition uses modified Fourier descriptors for the classification, of hand shapes. As always found in literature, such recognition systems consist of two phases: training and recognition. In our new practical approach, following the chosen appearance-based model, training and recognition is done in an interactive supervised way: the adaptation for untrained gestures is also solved by hand signals. Our experimental results with three different users are reported. In this paper, besides describing the recognition itself, we demonstrate our interactive training method in a practical application. © 2002 IEEE.

关键词： Gesture recognition

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Picture segmentation with introducing an anisotropic preliminary step to an MRF model with cellular neural networks

Picture segmentation with introducing an anisotropic prelimi...

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International Conference on Pattern Recognition

作者： T. Sziranyi L. Czuni Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Department of Image Processing and Neurocomputing University of Veszprém Hungary

Due to the large computation power needed for Markovian random field (MRF) based image processing, new variations of the basic MRF model are implemented. The transportation of the model to the very fast cellular neural networks (CNN) gave new tasks and opportunities to improve the technique, since the CNN has a special local architecture. This CNN architecture can be implemented in real VLSI circuits of superior speed in image processing. A type of MRF image segmentation with modified metropolis dynamics (MMD) can be well implemented in the CNN architecture. In this paper we address the improvement of this existing CNN method by introducing anisotropic diffusion as the smoothing process in the model. We suggest that this new feature with the MRF representation will give a new approach to solving early vision problems in the future.

关键词： Anisotropic magnetoresistance Cellular neural networks image segmentation image processing Computer networks Pixel Labeling Smoothing methods Laboratories Automation

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