In this paper, we propose a new method of representation of on-line signatures by clustering of signatures. Our idea is to provide better representation by clustering of signatures based on global features. Global fea...
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Distance measures between statistical models or between a model and observations are widely used concepts in signal processing. they are commonly used in solving problems such as detection, automatic segmentation, cla...
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ISBN:
(纸本)0780379462
Distance measures between statistical models or between a model and observations are widely used concepts in signal processing. they are commonly used in solving problems such as detection, automatic segmentation, classification, patternrecognition and coding. In recent years, there has been an interest in extending these distance measures to the time-frequency plane. It has been suggested that these measures can be used for discriminating between nonstationary signals based on their time-frequency representations. In this paper, several well-known distance measures from information theory will be adapted to the time-frequency plane. the application of these measures for signal detection will be presented. the performance of these measures will be illustrated through an example.
In this paper we analyse theoretical foundations of syntactic patternrecognition and its relationships with mathematical linguistics, structural patternrecognition, and statistical patternrecognition. We point out ...
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In this paper we explore how a spectral technique suggested by quantum walks can be used to distinguish non-isomorphic cospectral graphs. Reviewing ideas from the field of quantum computing we recall the definition of...
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the proceedings contain 17 papers. the special focus in this conference is on representations, Analysis and recognition of Shape and Motion from Imaging Data. the topics include: Rapid urban 3D modeling for drone-base...
ISBN:
(纸本)9783030198152
the proceedings contain 17 papers. the special focus in this conference is on representations, Analysis and recognition of Shape and Motion from Imaging Data. the topics include: Rapid urban 3D modeling for drone-based situational awareness assistance in emergency situations;Defining mesh-LBP variants for 3D relief patterns classification;a normalized generalized curvature scale space for 2D contour representation;a new watermarking method based on analytical clifford fourier mellin transform;simultaneous semi-supervised segmentation of category-independent objects from a collection of images;brenier approach for optimal transportation between a quasi-discrete measure and a discrete measure;Global and regional deformation analysis of the myocardium: MRI data application;On the reliability of LSTM-MDL models for pedestrian trajectory prediction;pedestrian tracking in the compressed domain using thermal images;an image processing framework for automatic tracking of wave fronts and estimation of wave front velocity for a gas experiment;the algorithm and software for timber batch measurement by using image analysis;stereo matching confidence learning based on multi-modal convolution neural networks;multi-person head segmentation in low resolution crowd scenes using convolutional encoder-decoder framework;crossEncoder: Towards 3D-free depth face recovery and fusion scheme for heterogeneous face recognition;neural approach for context scene image classification based on geometric, texture and color information.
作者:
Lefèvre, SébastienLSIIT
CNRS University Louis Pasteur Strasbourg i Parc d'Innovation Bvd Brant 67412 Illkirch Cedex France
Morphological signatures are powerful descriptions of the image content which are based on the framework of mathematical morphology. these signatures can be computed on a global or local scale: they are called pattern...
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ISBN:
(纸本)9789728865931
Morphological signatures are powerful descriptions of the image content which are based on the framework of mathematical morphology. these signatures can be computed on a global or local scale: they are called pattern spectra (or granulometries and antigranulometries) when measured on the complete images and morphological profiles when related to single pixels. their goal is to measure shape distribution instead of intensity distribution, thus they can be considered as a relevant alternative to classical intensity histograms, in the context of visual patternrecognition. A morphological signature (either a pattern spectrum or a morphological profile) is defined as a series of morphological operations (namely openings and closings) considering a predefined pattern called structuring element. Even if it can be used directly to solve various patternrecognition problems related to image data, the simple definitions given in the binary and grayscale cases limit its usefulness in many applications. In this paper, we introduce several 2-D extensions to the classical 1-D morphological signature. More precisely, we elaborate morphological signatures which try to gather more image information and do not only include a dimension related to the object size, but also consider on a second dimension a complementary information relative to size, intensity or spectral information. Each of the 2-D morphological signature proposed in this paper can be defined either on a global or local scale and for a particular kind of images among the most commonly ones (binary, grayscale or multispectral images). We also illustrate these signatures by several real-life applications related to object recognition and remote sensing.
In this paper, we present a novel approach that assists in the task of data-parallel patternrecognition. the classification of program code into parallel patterns relies mainly in the extraction of characteristics th...
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In this paper, an incremental algorithm which is derived from Non-negative Matrix Factorization (NMF) is proposed for background modeling in surveillance type of video sequences. the adopted algorithm, which is called...
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ISBN:
(纸本)9789728865931
In this paper, an incremental algorithm which is derived from Non-negative Matrix Factorization (NMF) is proposed for background modeling in surveillance type of video sequences. the adopted algorithm, which is called as Incremental NMF (INMF), is capable of modeling dynamic content of the surveillance video and controlling contribution of the subsequent observations to the existing representation properly. INMF preserves additive, parts-based representation, and dimension reduction capability of NMF without increasing the computational load. Test results are reported to compare background modeling performances of batch-mode and incremental NMF in surveillance type of video. Moreover, test results obtained by the incremental PCA are also given for comparison purposes. It is shown that INMF outperforms the conventional batch-mode NMF in all aspects of dynamic background modeling. Although object tracking performance of INMF and the incremental PCA are comparable, INMF is much more robust to illumination changes.
When a classifier is used to classify objects, it is important to know if these objects resemble the training objects the classifier is trained with. Several methods to detect novel objects exist. In this paper a new ...
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A new method is proposed for selection of the optimal number of components of a mixture model for pattern classification. We approximate a class-conditional density by a mixture of Gaussian components. We estimate the...
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