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International Symposium on Signal processing and Its Applications (ISSPA)

作者： Ramin Tajallipour Khan Wahid Multimedia Processing and Prototyping Laboratory Department of Electrical and Computer Engineering University of Saskatchewan SAS Canada

The paper presents an efficient data encoder based on Lempel-Ziv-Welch (LZW) algorithm to be used in a low-power capsule endoscopic system. The encoder is library-based where the size of the library can be set by the user, and hence, the output data rate can be controlled according to the bandwidth requirement. The simulation is carried out with several endoscopic images and the results show that a minimum overall compression ratio of 92.8% can be achieved with a minimum reconstruction quality of 30dB. The energy consumption has been estimated to be 75uJ/frame. Several other encoding algorithms have been studied and the comparative results are discussed.

关键词： Dictionaries Chromium Image resolution Discrete cosine transforms multimedia communication Impedance matching Encoding

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Hybrid DWT-DCT algorithm for biomedical image and video compression applications

Hybrid DWT-DCT algorithm for biomedical image and video comp...

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International Symposium on Signal processing and Its Applications (ISSPA)

作者： Suchitra Shrestha Khan Wahid Multimedia Processing and Prototyping Laboratory Department of Electrical and Computer Engineering University of Saskatchewan SAS Canada

Digital image and video in their raw form require an enormous amount of storage capacity. Considering the important role played by digital imaging and video in medical and health science, it is necessary to develop a system that produces high degree of compression while preserving critical image/video information. In this paper, we present a hybrid algorithm that performs the discrete cosine transform on the discrete wavelet transform coefficients. Simulation has been carried out on several medical and endoscopic images and videos. The results show that the proposed hybrid algorithm performs much better in term of peak-signal-to-noise-ratio with a higher compression ratio compared to standalone DCT and DWT algorithms. The scheme is intended to be used as the image/video compressor engine in medical imaging and video applications, such as, telemedicine and wireless capsule endoscopy.

关键词： Image resolution Larynx Biomedical imaging Quantization Discrete wavelet transforms Computed tomography

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Enhanced weakly trained frontal face detector for surveillance purposes

Enhanced weakly trained frontal face detector for surveillan...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Wael Louis K. N. Plataniotis Yong Man Ro Multimedia Laboratory Edward S. Rogers Department of Electrical and Computer Engineering University of Toronto Toronto Canada Image and Video System Laboratory Korea Advanced Institute of Science and Technology Daejeon South Korea

Face detection is becoming popular in surveillance applications; however, the need of enormous size face/non-face dataset, large number of features, and long training time are persistent problems. This paper claims that only a subset of the total number of features conserves the major power to detect faces; hence, this subset is capable to detect faces with high detection rate. The proposed detector fuses the results of two classifiers where one is trained with only 40 Haar-like features and the other is trained with only 50 LBP Histogram features. A pre-processing stage of skin-tone detection is applied to reduce the false positive rate. The detector is examined on real-life low-resolution surveillance sequence. Conducted experiments show that the proposed detector can achieve a high detection rate and a low false positive rate. Also, it outperforms Lienhart detector and tolerates wide range of illumination and blurring changes.

关键词： Feature extraction Face Detectors Histograms Pixel Training Face detection

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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...

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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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Color quantization using principal components for initialization of Kohonen SOFM

Color quantization using principal components for initializa...

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IEEE International Conference on Image processing

作者： Dimitris Mavridis Nikos Papamarkos Image Processing and Multimedia Laboratory Department of Electrical & Computer Engineering Democritus University of Thrace Greece

A new method is proposed for initializing Kohonen's self-organizing feature maps (SOFM) of fixed zero neighborhood radius for use in color quantization. The method employs the two largest principal components of the input image so that the initial weights of a number of neurons approach the input image color distribution. The rest of the neurons are initialized using the smallest principal component of the input image. Namely, standard SOFM is applied to the projection of the input image pixels onto the plane spanned by the two largest principal components and to pixels of the original image defined by the smallest principal component. The neuron values which emerge initialize the final SOFM of fixed zero neighborhood radius that performs the color quantization of the original image. Experimental results show that the proposed method can often produce smaller quantization errors than standard SOFM and other color quantization methods.

关键词： Quantization Neurons Neural networks Pixel Image color analysis Image processing Clustering algorithms Fuzzy neural networks Vectors Lattices

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Signal processing for neural spike trains

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Computational intelligence and neuroscience 2010年第1期2010卷 698751页

作者： Theodore W Berger Zhe Sage Chen Andrzej Cichocki Karim G Oweiss Rodrigo Quian Quiroga Nitish V Thakor Department of Biomedical Engineering Viterbi School of Engineering University of Southern California Los Angeles CA 90089 USA Neuroscience Statistics Research Laboratory Massachusetts Institute of Technology Cambridge MA 02139 USA Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Wako-shi Saitama 351-0198 Japan Department of Electrical and Computer Engineering Michigan State University MI 48824 USA Department of Engineering University of Leicester Leicester LE1 7RH UK School of Medicine Johns Hopkins University Baltimore MD 21205 USA

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Achieving Close-Capacity Performance with Simple Concatenation Scheme on Multiple-Antenna Channels

Achieving Close-Capacity Performance with Simple Concatenati...

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GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

作者： Nghi H. Tran Tho Le-Ngoc Tad Matsumoto Ha H. Nguyen Department of Electrical & Computer Engineering McGill University Montreal QUE Canada Information Theory and Signal Processing Laboratory School of Information Science Japan Advanced Institute of Science and Technology Japan Department of Electrical & Computer Engineering University of Saskatchewan Saskatoon SAS Canada

This paper proposes a simple yet capacity-approaching concatenation of a mixture of short memory length convolutional codes and simple rate-1 block code followed by either complex 1-dimensional (1-D) anti-Gray or Gray mapping over multiple antenna channels with quadrature phase-shift keying (QPSK). By interpreting rate-1 code together with 1-D mapping as a multi-D mapping employed over multiple transmit antennas, the error performance is analyzed in two regions, the error-floor and turbo pinch-off regions. In the former one, a tight union bound and design criterion on the asymptotic performance are first derived, which provide an useful tool to predict the error performance. Based on the design criterion, an optimal rate-1 code for each 1-D mapping is then constructed to achieve the best asymptotic performance. In the turbo pinch-off area, by using extrinsic information transfer (EXIT) chart, the most suitable mixed codes are selected for both symmetric and asymmetric antenna setups. It is demonstrated that the simple concatenation scheme can achieve near-capacity. Furthermore, its error performance is comparable to that obtained by using well-designed irregular low-density parity-check (LDPC) and repeat accumulate (RA) codes, and thereby, outperforms a scheme employing a parallel concatenated turbo code.

关键词： Parity check codes Convolutional codes Block codes Phase shift keying Quadrature phase shift keying Transmitting antennas Error analysis Performance analysis Concatenated codes Turbo codes

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Face annotation for personal photos using collaborative face recognition in online social networks

Face annotation for personal photos using collaborative face...

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International Conference on Digital Signal processing (DSP)

作者： JaeYoung Choi Wesley De Neve Yong Man Ro Konstantinos N. Plataniotis Image and Video Systems Laboratory Korea Advanced Institute of Science and Technology Daejeon South Korea Multimedia Laboratory The Edward S. Rogers Sr. Department of Electrical and Computer Engineering (ECE) University of Toronto Toronto ONT Canada

Automatic face annotation (or tagging) facilitates improved retrieval and organization of personal photos in online social networks. In this paper, we present a new collaborative face recognition (FR) method that aims to improve face annotation accuracy. The proposed method makes efficient use of multiple FR engines and databases that are distributed over an online social network. The performance of our collaborative face recognition method was successfully evaluated using the standard MPEG-7 VCE-3 data set and a set of real-world personal photos from the Web. The efficacy of the proposed method is demonstrated in terms of comparative annotation performance against non-collaborative approaches utilizing a single FR engine and a single database only.

关键词： Face Databases Social network services Context Feature extraction Communities Engines

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Development and Evaluation of Text Localization Techniques Based on Structural Texture Features and Neural Classifiers

Development and Evaluation of Text Localization Techniques B...

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International Conference on Document Analysis and Recognition

作者： Christos Emmanouilidis Costas Batsalas Nikos Papamarkos Computational Systems Unit CETI/R. C. ATHENA Xanthi Greece Image Processing and Multimedia Laboratory Department of Electrical & Computer Engineering Democritus University of Thrace Xanthi Greece Democritus University of Thrace Komotini GR

ISBN: (纸本)9781424445004

This paper presents a text localization approach for binarized printed document images. Emphasis is given to the feature extraction and feature selection stages. In the former, several document structure elements and spatial features, likely to convey useful information, are extracted. In the latter, evolutionary multi-objective feature selection is employed to identify combinations of features with simultaneous good performance in terms of text localization sensitivity and specificity. The selected features are applied to a range of classifiers. Performance results over document image sets from known databases are presented, employing the classifiers with or without feature selection. The results suggest that the hybrid techniques, which utilize the classifiers in combination with the customized pre-processing, feature extraction and feature selection stages, exhibit promising performance on a range of document images.

关键词： Feature extraction Data mining Image segmentation Text analysis Image analysis Image texture analysis Sensitivity and specificity Support vector machines Support vector machine classification Image recognition

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Estimation of proper parameter values for document binarization

Estimation of proper parameter values for document binarizat...

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10th IASTED International Conference on computer Graphics and Imaging, CGIM 2008

作者： Badekas, E. Papamarkos, N. Image Processing and Multimedia Laboratory Department of Electrical and Computer Engineering Democritus University of Thrace 67100 Xanthi Greece

ISBN: (纸本)9780889867192

Most of the existing document-binarization techniques deal with many parameters that require a priori setting of their values. Due to the unknown of the ground-truth images, the evaluation of document binarization techniques is subjective and employs human observers for the estimation of the appropriate parameter values. The selection of the appropriate values for these parameters is crucial and influences to the final binarization. However, there is no predetermined set of parameters that guarantees optimal binarization for all document images. This paper proposes a new technique that allows the estimation of proper parameters values for each one of the document binarization techniques. The proposed approach is based on a statistical performance analysis of a set of binarization results, which are obtained by applying various binarization techniques with different parameter values. The proposed statistical performance analysis can also depicts the best document binarization result obtained by a set of document binarization techniques.

关键词： Parameter estimation

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