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Gaussian modeling and Discrete Cosine Transform for efficient and automatic palmprint identification

Gaussian modeling and Discrete Cosine Transform for efficien...

引用

International Conference on Machine and Web Intelligence (ICMWI)

作者： Abdallah Meraoumia Salim Chitroub Ahmed Bouridane Signal and Image Processing Laboratory Electronics and Computer Science Faculty University of Sciences and Technology Houari Boumediene Bab-Ezzouar Algeria School of Computing Engineering and Information Sciences Northumbria University Newcastle-upon-Tyne UK

Automatic personal identification using biometric information is playing a more and more important role in applications such as public security, access control, banking, etc. Palmprint identification is a subcategory of biometrics identification, which can efficiently used to identify the people. It is for this reason that palmprint-based identification is becoming increasingly popularity in recent years. In this paper, we present a novel scheme for palmprint identification using the multi-variate Gaussian Probability Density Function (GPDF) and two-dimensional Block based Discrete Cosine Transform (2D-BDCT). In this method, a palmprint is firstly divided into overlapping and equal-sized blocks, and then, applies the discrete cosine transform over each block. By using zigzag scan order (starting at the top-left) each transform block is reordered to produce the observation vector. Subsequently, we use the Gaussian probability density function for modeling the feature vector of each palmprint. Finally, Log-likelihood scores are used for palmprint matching. The proposed scheme is validated for their efficacy on PolyU palmprint database of 100 users. Our experimental results show the effectiveness and reliability of the proposed approach, which brings both high identification accuracy rate.

关键词： Feature extraction Discrete cosine transforms Databases Accuracy Hidden Markov models Probability density function

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A robust face detection method using intrinsic images and an energy minimization technique under the near-IR light spectrum

A robust face detection method using intrinsic images and an...

引用

2009 International Conference on Image processing, computer Vision, and Pattern Recognition, IPCV 2009

作者： Lahlou, Mouncef Adjouadi, Malek Barreto, Armando Center for Advanced Technology and Education Department of Electrical and Computer Engineering Florida International University Miami FL United States Digital Signal Processing Laboratory Department of Electrical and Computer Engineering Florida International University Miami FL United States

ISBN: (纸本)9781601321190

Detecting faces accurately under natural lighting conditions remains a challenging task for advancing the performance of face recognition systems. Most face detection algorithms are associated with visible spectrum imagery which compromises their efficiency when image acquisition is subject to variable illumination. In this study, we propose a simple yet powerful solution that uses multiple cues to detect and locate faces accurately in near infrared (NIR) imaging systems. Specific objectives include (I) extract optimally the illumination and reflectance components of the original image using an intrinsic images decomposition technique, (2) modify the segmentation process by using an energy minimization procedure in an adaptive fashion, and (3) propose an enhanced face detection process on the basis of pupil localization. The evaluation of our face detector on image sequences of 45 different subjects from the CBSR NIR face dataset demonstrated a highly competitive accuracy with less than 5% error rate.

关键词： Face recognition

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Reflectance measurement system for skin color modeling in chromaticity color space

Reflectance measurement system for skin color modeling in ch...

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2009 16th International Conference on Systems, signals and Image processing, IWSSIP 2009

作者： Kramberger, Iztok University of Maribor Faculty of Electrical Engineering and Computer Science Laboratory for Digital and Information Systems Smetanova ulica 17 SI-2000 Maribor Slovenia

ISBN: (纸本)9781424445301

Experimental skin reflectance measurement setup is presented to acquire skin color signals under different illuminant conditions directly by an image sensor. To obtain stimulus of varying illuminant conditions an adjustable RGB light source is used. Skin color modeling is an important step for efficient skin color image segmentation, which plays an important role when defining regions of interest in image sequence for a successful hand tracking and gesture recognition within spatially defined vision based interaction. To improve detection accuracy of pixel based skin color segmentation a parametric skin color model can be used, which is able to adapt different illuminant conditions. Therefore skin reflectance under different illuminants plays an important role to obtain such a model. Experimental results of hand skin reflectance measurements within chromaticity space are shown. ©2009 IEEE.

关键词： Color

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Reflectance Measurement System for Skin Color Modeling in Chromaticity Color Space

Reflectance Measurement System for Skin Color Modeling in Ch...

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International Conference on Systems, signals and Image processing, IWSSIP

作者： Iztok Kramberger Faculty of Electrical Engineering and Computer Science Laboratory for Digital and Information Systems University of Maribor Maribor Slovenia

关键词： Reflectivity Skin Extraterrestrial measurements Image segmentation Streaming media Image sensors Color Feature extraction computer vision Electric variables measurement

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Multi channel EOG signal recognition for an embedded eye movement tracking device

Multi channel EOG signal recognition for an embedded eye mov...

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2009 16th International Conference on Systems, signals and Image processing, IWSSIP 2009

作者： Kirbiš, Matej Kramberger, Iztok ASTRON d.o.o. RND Company Jadranska cesta 27 SI-2000 Maribor Slovenia University of Maribor Faculty of Electrical Engineering and Computer Science Laboratory for Digital and Information Systems Smetanova ulica 17 SI-2000 Maribor Slovenia

ISBN: (纸本)9781424445301

In this paper we describe a low cost embedded system for eye movement tracking that supports disabled persons with basic interaction with Bluetooth enabled electronic devices. The method is based on tracking the EOG potential. The device has a built-in 32-bit RISC processor that performs acquisition of multichannel differential EOG signals and signal recognition. signal recognition is based on cross correlation principle where a simplified triangulated linear model for eye movement is used as a reference signal. The eye movement recognition is more or less user independent, but it takes some time and practice to become familiar with the system for efficient use. The embedded eye movement tracking device communicates with other devices via personal network, which is based on Bluetooth wireless technology. The communication protocol at the application level has been simplified in order to gain plain integration with other devices.

关键词： Eye movements

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Multi Channel EOG signal Recognition for an Embedded Eye Movement Tracking Device

Multi Channel EOG Signal Recognition for an Embedded Eye Mov...

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International Conference on Systems, signals and Image processing, IWSSIP

作者： Matej Kirbis Iztok Kramberger ASTRON d.o.o. RND Company Maribor Slovenia Faculty of Electrical Engineering and Computer Science Laboratory for Digital and Information Systems University of Maribor Maribor Slovenia

关键词： Electrooculography Tracking Skin Image segmentation Streaming media Reflectivity Image sensors Color Feature extraction computer vision

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Optical disc detection in retinal images

Optical disc detection in retinal images

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11th International Conference on Optimization of electrical and Electronic Equipment, OPTIM 2008

作者： Ivanovici, M. Scurtu, V. Computers and Electronics Department Faculty of Electrical Engineering and Computer Science Transilvania University Brasov Romania IEEE IEEE Signal Processing and Communications Societies

ISBN: (纸本)1424415446

Lasers are currently used for a wide spectrum of medical applications, including the treatment of eye disorders. When combined with digital image processing techniques, the issue of retinal image segmentation becomes of high importance. In this paper, our purpose is twofold: i) to identify and briefly present the existing approaches for the retinal image segmentation and ii) to test our hypothesis that the Viola-Jones algorithm - initially designed for face detection - can be suited as well for optical disc detection.

关键词： Medical applications

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Comparison of Speaker Segmentation Methods Based on the Bayesian Information Criterion and Adapted Gaussian Mixture Models

Comparison of Speaker Segmentation Methods Based on the Baye...

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International Conference on Systems, signals and Image processing

作者： Matej Grasic Marko Kos Andrej Zgank Zdravko Kacic University of Maribor Faculty of Electrical Engineering and Computer Science Laboratory for Digital Signal Processing Smetanova ul. 17 SI-2000 Maribor Slovenia

ISBN: (纸本)9788022728560

This paper addresses the topic of unsupervised speaker segmentation for automatic speech recognition in a complex real life environment like broadcast news domain. A statistical approach where a Universal Background Model (UBM) is applied for online speaker segmentation was compared with the widely used Bayesian Information Criterion (BIC) approach. An analysis of influence of different window selection strategies on performance of both methods was carried out. Experiments and test evaluation were performed on the Slovenian BNSI Broadcast News speech database.

关键词： Bayesian Information Criterion (BIC) Speaker segmentation Gaussian Mixture Models (GMM) Broadcast news

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Speech Bandwidth Classification for Broadcast News Domain Using Artificial Neural Network and Gaussian Mixture Models

Speech Bandwidth Classification for Broadcast News Domain Us...

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International Conference on Systems, signals and Image processing

作者： Marko Kos Matej Grasic Bojan Kotnik Zdravko Kacic University of Maribor Faculty of Electrical Engineering and Computer Science Laboratory for Digital Signal Processing Smetanova ul. 17 SI-2000 Maribor Slovenia

ISBN: (纸本)9788022728560

In this paper we present research work that was carried out on Slovenian BNSI Broadcast News database regarding the speech bandwidth classification. Speech recorded in studio environment has frequency bandwidth of 8kHz, while speech recorded over telephone channel has the bandwidth of 3.1kHz. Speech bandwidth classification enables us to use separate speech models for automatic speech recognition (ASR), which helps to improve the overall automatic speech recognition result. For the task of speech bandwidth classification we used two different model-based principles. One principle is based on artificial neural network and the second principle is based on Gaussian mixture models. Both principles have been tested and evaluated using same front-end features for simple result comparison.

关键词： Classification Bandwidth Artificial neural networks Gaussian mixture models Broadcast news Artificial neural networks Bandwidth Speech Mixture models Speech recognition frequency band widths Taxonomy news

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TerraSAR-X: Complex Image Inversion for Feature Extraction

TerraSAR-X: Complex Image Inversion for Feature Extraction

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Matteo Soccorsi Mihai Datcu Dusan Gleich German Aerospacec Center Remote Sensing Technology Institute Wessling Germany Laboratory for Signal Processing and Remote Control Faculty of Electrical Engineering and Computer Science University of Maribor Slovenia

In this paper we present two algorithms for information extraction from Single Look Complex (SLC) Synthetic Aperture Radar (SAR) images. The first algorithm is based on Tikhonov regularization with Total Variation (TV) and a Point-Based Feature (PBF) term. Based on the equivalence of Tikhonov and the Bayesian estimate, the second algorithm is a Maximum A Posteriori (MAP) estimation with a complex-valued Gauss-Markov Random Field (GMRF) in addition to the TV prior. The first algorithm produces a despeckled image preserving fine details and texture. The second algorithm gives a denoised image and in addition the estimated feature parameter vector thetas.

关键词： Feature extraction Synthetic aperture radar signal processing algorithms TV Bayesian methods Image restoration Adaptive filters Cost function Anisotropic magnetoresistance Speckle

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