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Salient spectral features for points detection
2016 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), 2016In this paper we introduce a novel method for detecting salient features points on 3D meshes. The contribution of the proposed method is to detect salient feature points in the dual graph spectral domain instead of spatial one. A dual graph Laplacian spectrum of 3D shape is firstly computed for each triangles of the shape. Then we compute the geometric
Nabi Habiba, Ali Douik
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Spectral features for Arabic word recognition
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002We present a holistic technique for recognising words written in cursive Arabic script that does not rely on character segmentation. Each word is transformed into a normalised polar image, and a two dimensional Fourier transform is applied to the polar image. The resultant spectrum tolerates variations in size, rotation or displacement.
Mohammad S. Khorsheed +1 more
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Using spectral features for modelbase partitioning
Proceedings of 13th International Conference on Pattern Recognition, 1996We present an eigenvalue or spectral representation for CAD models to be used in conjunction with the more traditional attributed graph based representation of these models. The eigenvalues provide a gross description of the structure of the objects, and help to divide a large modelbase into structurally homogeneous partitions. Models in each partition
Kuntal Sengupta, Kim L. Boyer
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Evaluation of skin spectral features for biometrie
2017 IEEE 2nd International Conference on Signal and Image Processing (ICSIP), 2017In the recent years, multispectral imaging has been successfully used in various biometric authentication applications. However, in most cases, the frames of multispectral images are consolidated simply by using data fusion techniques rather than contributing directly to the recognition process.
Li, Chao +4 more
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Channel compensation of modulation spectral features
Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03., 2003We propose a new channel compensation method for modulation spectral features. We compare our proposed method, subband normalization, with a more traditional method, cepstral mean subtraction (CMS). Experimental results show that subband normalized modulation scale features provide advantages over CMS features. The proposed method is not only robust to
Somsak Sukittanon, Les E. Atlas
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Bi-Level Spectral Feature Selection
IEEE Transactions on Neural Networks and Learning SystemsUnsupervised feature selection (UFS) aims to learn an indicator matrix relying on some characteristics of the high-dimensional data to identify the features to be selected. However, traditional unsupervised methods perform only at the feature level, i.e., they directly select useful features by feature ranking.
Zebiao Hu +4 more
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Spectral Features for Synthetic Speech Detection
IEEE Journal of Selected Topics in Signal Processing, 2017Recent advancements in voice conversion (VC) and speech synthesis research make speech-based biometric systems highly prone to spoofing attacks. This can provoke an increase in false acceptance rate in such systems and requires countermeasure to mitigate such spoofing attacks.
Dipjyoti Paul +2 more
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1997
The goal of pattern analysis, in general, is to transform signals into symbolic descriptions [Dud73, Nie90a, Pen86]. For simple classification problems this corresponds to the computation of a class number for an observed signal (c.f. Figure 6.1). Since the amount of data is too high, if images or speech signals are used directly, the signals are ...
Dietrich W. R. Paulus, Joachim Hornegger
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The goal of pattern analysis, in general, is to transform signals into symbolic descriptions [Dud73, Nie90a, Pen86]. For simple classification problems this corresponds to the computation of a class number for an observed signal (c.f. Figure 6.1). Since the amount of data is too high, if images or speech signals are used directly, the signals are ...
Dietrich W. R. Paulus, Joachim Hornegger
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Face recognition using spectral features
Pattern Recognition, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fei Wang 0001 +3 more
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Analytical feature extraction and spectral summation
Proceedings of 13th International Conference on Pattern Recognition, 1996We propose a formalism for analysing multilayer perceptron (MLP) networks as propagations of binary transitions along excitatory and inhibitory sensitised paths. By characterising a Boolean function as sets of detected transitions, we produce a spectral summation and construct a network from the derived weight constraints.
Terry Windeatt, Robert Tebbs
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