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IEEE international Conference on image processing

作者： T. Tanaka Y. Yamashita School of Science and Engineering Tokyo Institute of Technology Meguro Tokyo Japan

A lapped biorthogonal transform adapted for local directionality of an image is proposed. The proposed transform consists of overlapping basis functions and non-overlapping basis functions, where the basis functions' centers of symmetry are aligned. Because of the alignment, we can treat the image boundaries without special processing. In order to construct non-overlapping basis functions, we also introduce a transform that provides the optimal approximation of an original signal in a given subspace. In image coding, an image block is selectively transformed by one of the orientation adaptive transforms. Experimental results show that the use of adaptation improves the quality of decoded images.

关键词： image coding Decoding Data compression Transform coding image edge detection Bit rate image reconstruction Matrix decomposition Symmetric matrices Bismuth

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Advances in iterative multigrid PIV image processing

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EXPERIMENTS IN FLUIDS 2000年第Sup1期29卷 S51-S60页

作者： Scarano, F Riethmuller, ML Von Karman Inst Fluid Dynam Dept Environm & Appl Fluid Dynam B-1640 Rhode St Genese Belgium

An image-processing technique is proposed, which performs iterative interrogation of particle image velocimetry (PIV) recordings. The method is based on cross-correlation, enhancing the matching performances by means of a relative transformation between the interrogation areas. On the basis of an iterative prediction of the tracers motion, window offset and deformation are applied, accounting for the local deformation of the fluid continuum. In addition, progressive grid refinement is applied in order to maximise the spatial resolution. The performances of the method are analysed and compared with the conventional cross correlation with and without the effect of a window discrete offset. The assessment of performance through synthetic PIV images shows that a remarkable improvement can be obtained ill terms of precision and dynamic range. Moreover, peak-locking, effects do not affect the method in practice. The velocity gradient range accessed with the application of a relative window deformation (linear approximation) is significantly enlarged, as confirmed in the experimental results.

关键词： Discrete window offset Velocimetry Improvement Limitation Accuracy

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Advances in iterative multigrid PIV image processing

Advances in iterative multigrid PIV image processing

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3rd international workshop on Particle image Velocimetry

作者： Scarano, F Riethmuller, ML Von Karman Inst Fluid Dynam Dept Environm & Appl Fluid Dynam B-1640 Rhode St Genese Belgium

关键词： Iterative methods

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Neural network based photometric stereo for object with non-uniform reflectance factor

Neural network based photometric stereo for object with non-...

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international Conference on Neural Information processing

作者： Y. Iwahori R.J. Woodham M. Shoaib Bhuiyan N. Ishii Faculty of Engineering Nagoya Institute of Technology Nagoya Japan Department of Computer Science University of British Columbia Vancouver BC Canada

Proposes a new neural network-based photometric stereo approach for objects with a non-uniform reflectance factor using four input images acquired under different illumination conditions. The approach is empirical and uses the radial basis function (RBF) neural network to perform non-parametric functional approximation. We exploit the redundancy inherent in the four image irradiance values measured at each surface point in order to determine a local confidence estimate. This is achieved by training two distinct neural networks from a calibration sphere. The first neural network maps the image irradiance to both the surface normal and the reflectance factor (albedo). The second network maps the surface normal and the reflectance factor to the image irradiance. A comparison between the actual input and the inversely predicted input is used as the confidence estimate. Experiments on real data are described.

关键词： Neural networks Photometry Reflectivity Calibration Light sources Table lookup Least squares approximation Shape Lighting Testing

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image recognition using a directions field technique

Image recognition using a directions field technique

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6th international workshop on Digital image processing and Computer Graphics (DIP-97) - Applications in Humanities and Natural Sciences

作者： Soifer, VA Kotlyar, VV Khonina, SN Khramov, AG Skidanov, RV Russian Acad Sci Image Proc Syst Inst Samara 443001 Russia

ISBN: (纸本)0819427934

An approach to the interpretation and recognition of images based on the directional field is developed. A model of an image with structure redundancy is introduced. Digital methods for the construction of the directional field, including the method of local quadratic approximation, the spectral method, and the variance method, are considered. An optical scheme for the construction of the directional field with the use of radial segment spatial Filters is presented. The developed approach is tested in the analysis of fingerprint images, tear crystallograms and interferograms.

关键词： pattern recognition directions field fingerprint and interferogram analysis

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local Edge Detection from Histogram Evaluation via Minimum Description Length Principle

Local Edge Detection from Histogram Evaluation via Minimum D...

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4th international Conference on Computer Science and Informatics, JCIS 1998, 1st international workshop on High Performance, 1st international workshop on Computer Vision, Pattern Recognition and image processing Volume 4

作者： Klose, Aljoscha Department of Computer Science University of Magdeburg Germany

An approach for local edge detection with the help of local histogram evaluation is discussed. The minimum description length (MDL) principle is applied to carry out the local edge detection. The data to be transmitted from sender to receiver are defined and different models are used to encode this data. It is observed that the MDL divides between edge and non-edge, without the need to choose a threshold.

关键词： Edge detection

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Precise edge detection: representation by Boolean functions, implementation on the CNN

Precise edge detection: representation by Boolean functions,...

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IEEE international workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： I.N. Aizenberg N.N. Aizenberg J. Vandewalle Department Elektrotechniek ESAT SISTA K.U. Leuven Heverlee Belgium Department of Cybernetics University of Uzhgorod Uzhgorod Ukraine Department Elektrotechniek ESATISISTA K.U. Leuven Heverlee Belgium

An edge detection problem is considered in the paper. It is proposed to reduce the edge detection problem on binary images to evaluation of the Boolean functions. A separate processing of the binary planes with their further integration into resulting image is used for edge detection on the gray-scale images. The different Boolean functions for detection of edges corresponding to the upward and downward brightness overleaps, to the narrow directions (south-north, south-east-north-west, etc.) are considered. All the processing functions are non-threshold Boolean functions of nine variables (such a number of variables corresponds to the processing within a 3/spl times/3 local window around the each pixel). Since all the functions are not threshold, CNN with universal binary neurons are proposed to be used for their implementation. The weighting templates for all functions are obtained by learning. The software simulation results are also presented.

关键词： image edge detection Boolean functions Cellular neural networks Brightness Gray-scale Neurons Discrete wavelet transforms Cybernetics image processing Laplace equations

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An irregular sampling algorithm adapted to the local frequency content of signals and the corresponding on-line reconstruction algorithm

An irregular sampling algorithm adapted to the local frequen...

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international Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： V. Filimon Daimler Benz Forschungszentrum Ulm Ulm Germany

The description of signals using wavelet transforms leads to useful time-frequency localization and possible signal compression. Based on the discrete wavelet transform (DWT) an adaptive sampling algorithm in the discrete time domain is constructed, by finding an univocal relation between the signal's samples and the non-zero transform coefficients of its DWT. Reconstruction is performed through repeated projections of an approximation of the initial signal based on the arriving samples, into the original signal's subspace, using the Neumann method of inverting bounded operators. Both adaptive sampling and reconstruction are on-line because of the finite support of the analyzing wavelets.

关键词： Sampling methods Frequency Discrete wavelet transforms Finite impulse response filter Signal analysis Wavelet domain Wavelet analysis image analysis Low pass filters Signal reconstruction

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Automated building extraction using dense elevation matrices

Automated building extraction using dense elevation matrices

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25th AIPR workshop on Emerging Applications of Computer Vision

作者： Bendett, AA Rauhala, UA Pearson, JJ GDE Systems Inc. (United States)

ISBN: (纸本)0819423661

The identification and measurement of buildings in imagery is important to a number of applications including cartography, modeling and simulation, and weapon targeting. Extracting large numbers of buildings manually can be time-consuming and expensive, so the automation of the process is highly desirable. This paper describes and demonstrates such an automated process for extracting rectilinear buildings from stereo imagery. The first step is the generation of a dense elevation matrix registered to the imagery. In the examples shown, this was accomplished using Global Minimum Residual Matching (GMRM). GMRM automatically removes gamma-parallax from the stereo imagery and produces a dense matrix of x-parallax values which are proportional to the local elevation, and, of course, registered to the imagery. The second step is to form a joint probability distribution of the image say levels and the corresponding height values from the elevation matrix. Based on the peaks of that distribution, the area of interest is segmented into feature and non-feature areas. The feature areas are further refined using length, width and height constraints to yield promising building hypotheses with their corresponding vertices. The gray shade image is used in the third step to verify the hypotheses and to determine precise edge locations corresponding to the approximate vertices and satisfying appropriate orthogonality constraints. Examples of successful application of this process to imagery are presented, and extensions involving the use of dense elevation matrices from other sources are possible.

关键词： image segmentation image processing Matrices image resolution image processing algorithms and systems 3D modeling Weapons 3D acquisition Cartography Modeling and simulation

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international workshop on Algebraic Frames for the Perception-Action Cycle, AFPAC 1997

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international workshop on Algebraic Frames for the Perception and Action Cycle, AFPAC 1997

ISBN: (纸本)3540635173

The proceedings contain 22 papers. The special focus in this conference is on PAC Systems, Low Level, Early Vision, Recognition of Visual Structure and processing of the 3D Visual Space. The topics include: Algebraic aspects of designing behaviour based systems;from multidimensional signals to the generation of responses;perception and action using multilinear forms;local image operators and iconic structure;on automatic selection of temporal scales in time-causal scale-space;some applications of representations of lie algebras and lie groups;a systematic approach to geometric-based grouping and non-accidentalness;multi dimensional signal processing using an algebraically extended signal representation;fractal basis functions for pattern recognition;algebraic and geometric tools to compute projective and permutation invariants;a unified language for computer vision and robotics;structure from translational observer motion;the cascaded Hough transform as support for grouping and finding vanishing points and lines;statistical optimization and geometric visual inference;path prediction and classification based on non-linear filtering and neural network approaches for perception and action.

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