- Two-way Planar Array Radar with Diamond- and X-shaped Configurations for Sidelobe Suppression
- Harmonic Trust Spectrum Modeling for Cognitive Radio Intrusion Detection
- Adaptive Entropy Prediction-based Lossless Compression for Efficient Data Transmission in Terrestrial and Underwater IoT Systems
- A Spatio-temporal Residual Attention Network with SNR-adaptive Weighting for MIMO-OFDM Channel Estimation
- Communication-efficient Embedded FFT Processing for Acoustic Telemetry in LPWAN-based Beehive Monitoring Systems
- FEC Hybrid Method Based on Reed–Solomon Codes for Transmitting Video Signal Over Limited Bandwidth and High Loss Rate Channels
- Dual Wide-band Microstrip Antenna for Wireless Communication Systems
- Network Threat Detection in IaaS Environments Based on Flow Log Data
- Machine Learning-based Automatic Modulation Classification for 5G-Advanced and 6G Waveforms: Robust Identification Under Realistic Channel Impairments
- Energy-delay Aware Data Collection in Mobile Sink-based Wireless Sensor Networks with Optimized Visiting Points and Two-level Data Aggregation
No. 4 (2010)
Published:
2010-12-30
Full Issue
ARTICLES FROM THIS ISSUE
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Preface
Abstract
This issue of the Journal of Telecommunications and Information Technology contains papers devoted to various aspects of biometrical authentication systems, and in particular, to iris, face, speech, and on-line signature biometrics, multi-biometrics, and biometric template formation. The papers in this issue deal also with certain issues of crosstalk propagation in silicon substrates and with some mobile networks problems. (...)
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Robust and Accurate Iris Segmentation Algorithm for Color and Noisy Eye Images
Abstract
Efficient and robust segmentation of iris images captured in the uncontrolled environments is one of the challenges of non-cooperative iris recognition systems. We address this problem by proposing a novel iris segmentation algorithm, which is suitable both for monochrome and color eye images. The method presented use modified Hough transform to roughly localize the possible iris and pupil boundaries, approximating them by circles. A voting mechanisms is applied to select a candidate iris regions. The detailed iris boundary is approximated by the spline curve. Its shape is determined by minimizing introduced boundary energy function. The described algorithm was submitted to the NICE.I iris image segmentation contest, when it was ranked 11th and 10th out of total 97.
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Iris Recognition System Based on Zak-Gabor Wavelet Packets
Abstract
The paper proposes a new iris coding method based on Zak-Gabor wavelet packet transform. The essential component of the iris recognition methodology design is an effective adaptation of the transformation parameters that makes the coding sensitive to the frequencies characterizing ones eye. We thus propose to calculate the between-to-within class ratio of weakly correlated Zak-Gabor transformation coefficients allowing for selection the frequencies the most suitable for iris recognition. The Zak-Gabor-based coding is non-reversible, i.e., it is impossible to reconstruct the original iris image given the iris template. Additionally, the inference about the iris image properties from the Zak-Gabor-based code is limited, providing a possibility to embed the biometric replay attack prevention methodology into the coding. We present the final prototype system design, including the hardware, and evaluate its performance using the database of 720 iris images.
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Image Preprocessing for Illumination Invariant Face Verification
Abstract
Performance of the face verification system depend on many conditions. One of the most problematic is varying illumination condition. In this paper 14 normalization algorithms based on histogram normalization, illumination properties and the human perception theory were compared using 3 verification methods. The results obtained from the experiments showed that the illumination preprocessing methods significantly improves the verification rate and it’s a very important step in face verification system.
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Face Tracking and Recognition with the Use of Particle-Filtered Local Features
Abstract
A consistent particle filtering-based framework for the purpose of parallel face tracking and recognition from video sequences is proposed. A novel approach to defining randomized, particle filtering-driven local face features for the purpose of recognition is proposed. The potential of cumulating classification decisions based on the proposed feature set definition is evaluated. By applying cumulation mechanisms to the classification results determined from single frames and with the use of particle-filtered features, good recognition rates are obtained at the minimal computational cost. The proposed framework can operate in real-time on a typical modern PC. Additionally, the application of cumulation mechanisms makes the framework resistant to brief visual distortions, such as occlusions, head rotations or face expressions. A high performance is also obtained on low resolution images (video frames). Since the framework is based on the particle filtering principle, it is easily tunable to various application requirements (security level, hardware constraints).
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Rule Based Speech Signal Segmentation
Abstract
This paper presents the automated speech signal segmentation problem. Segmentation algorithms based on energetic threshold showed good results only in noise-free environments. With higher noise level automatic threshold calculation becomes complicated task. Rule based postprocessing of segments can give more stable results. Off-line, on-line and extrema types of rules are reviewed. An extrema-type segmentation algorithm is proposed. This algorithm is enhanced by a rule base to extract higher energy level segments from noise. This algorithm can work well with energy like features. The experiments were made to compare threshold and rule-based segmentation in different noise types. Also was tested if multifeature segmentation can improve segmentation results. The extrema rule-based segmentation showed smaller error ratio in different noise types and levels. Proposed algorithm does not require high calculation resources. Such algorithm can be processed by devices with limited computing power.
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Speech Segmentation Algorithm Based on an Analysis of the Normalized Power Spectral Density
Abstract
This article demonstrates a new approach to speaker independent phoneme detection. The core of the algorithm is to measure the distance between normalized power spectral densities in adjacent, short-time segments and verify it based on velocity of changes of values of short-time signal energy analysis. The results of experiment analysis indicate that proposed algorithm allows revealing a phoneme structure of pronounced speech with high probability. The advantages of this algorithm are absence of any prior information on a signal or model of phonemes and speakers that allows the algorithm to be speaker independent and have a low computation complexity.
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Relaxing the WDO Assumption in Blind Extraction of Speakers from Speech Mixtures
Abstract
The time-frequency masking approach in blind speech extraction consists of two main steps: feature clustering in a space spanned over delay-time and attenuation rate, and spectrogram masking in order to reconstruct the sources. Usually a binary mask is generated under the strong W-disjoint orthogonal (WDO) assumption (disjoint orthogonal representations in the frequency domain). In practice, this assumption is most often violated leading to weak quality of reconstructed sources. In this paper we propose the WDO to be relaxed by allowing some frequency bins to be shared by both sources. As we detect instantaneous fundamental frequencies the mask creation is supported by exploring a harmonic structure of speech. The proposed method is proved to be effective and reliable in experiments with both simulated and real acquired mixtures.
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Hidden Signature for DTW Signature Verification in Authorizing Payment Transactions
Abstract
Traditional use of dynamic time warping for signature verification consists of forming some dissimilarity measure between the signature in question and a set of "template signatures". In this paper, we propose to replace this set with the hidden signature and use it to calculate the normalized errors of signature under verification. The approach was tested on the MCYT database, using both genuine signatures and skilled forgeries. Moreover, we present the real-world application of the proposed algorithm, namely the complete biometric system for authorizing payment transactions. The authorization is performed directly at a point of sale by the automatic signature verification system based on the hidden signature.
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Simulation Model of Biometric Authentication Using Multiagent Approach
Abstract
In this article authors present the concept of application of multiagent approach in modeling biometric authentication systems. After short introduction, we present a short primer to multiagent technology. Next, we depict current state of the art related to biometrics combined with multiagent approach. In the next part of the work we present four exemplary simulation models of biometric authentication environments as well as the results of their examination.
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Probabilistic Issues in Biometric Template Design
Abstract
Since the notion of biometric template is not well defined, various concepts are used in biometrics practice. In this paper we present a systematic view on a family of template concepts based on the L1 or L2 dissimilarities. In particular, for sample vectors of independent components we find out how likely it is for the median code to be a sample vector.
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The Template Selection in Biometric Systems Based on Binary Iris Codes
Abstract
Since the variability of data within readings from the same person is intrinsic property of every biometric system, the problem of finding a good representative – the template – was recognized and present since the beginning of biometrics. This problem was solved differently for different biometric types, yet usually the template somehow averages the collected data samples. However, for the iris type, the template is usually just one or a few samples. In this paper we describe the experiments that suggest that the averaging is also justified in case of iris template creation. This is an important fact, which can significantly improve a performance of biometric template protection methods for iris.
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Impact of Crosstalk into High Resistivity Silicon Substrate on the RF Performance of SOI MOSFET
Abstract
Crosstalk propagation through silicon substrate is a serious limiting factor on the performance of the RF devices and circuits. In this work, substrate crosstalk into high resistivity silicon substrate is experimentally analyzed and the impact on the RF behavior of silicon-on-insulator (SOI) MOS transistors is discussed. The injection of a 10 V peak-to-peak single tone noise signal at a frequency of 3 MHz ( fnoise) generates two sideband tones of −56 dBm separated by fnoise from the RF output signal of a partially depleted SOI MOSFET at 1 GHz and 4.1 dBm. The efficiency of the introduction of a trap-rich polysilicon layer located underneath the buried oxide (BOX) of the high resistivity (HR) SOI wafer in the reduction of the sideband noise tones is demonstrated. An equivalent circuit to model and analyze the generation of these sideband noise tones is proposed.
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Capacity and Quality Optimization of CDMA Networks
Abstract
Coverage and capacity are important issues in the planning process for cellular third generation (3G) mobile networks. The planning process aims to allow the maximum number of users sending and receiving adequate signal strength in a cell. This paper describes the conceptual expressions require for network coverage and capacity optimization analysis, examines service quality issues, and presents practical solutions to problems common to sub-optimality of CDMA networks.
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Routing Misbehavior Detection in MANETs Using 2ACK
Abstract
This paper proposes routing misbehavior detection in MANETs using 2ACK scheme. Routing protocols for MANETs are designed based on the assumption that all participating nodes are fully cooperative. However, due to the open structure and scarcely available battery-based energy, node misbehavior may exist. In the existing system, there is a possibility that when a sender chooses anintermediate link to send some message to a destination, the intermediate link may pose problems such as, the intermediate node may not forward the packets to destination, it may take very long time to send packets or it may modify the contents of the packet. In MANETs, as there is no retransmission of packets once it is sent, care must be taken not to loose packets. We have analyzed and evaluated a technique, termed 2ACK scheme to detect and mitigate the effect of such routing misbehavior in MANETs environment. It is based on a simple 2-hop acknowledgment packet that is sent back by the receiver of the next-hop link. 2ACK transmission takes place for only a fraction of data packets, but not for all. Such a selective acknowledgment is intended to reduce the additional routing overhead caused by the 2ACK scheme. Our contribution in this paper is that, we have embedded some security aspects with 2ACK to check confidentiality of the message by verifying the original hash code with the hash code generated at the destination. If 2ACK is not received within the wait time or the hash code of the message is changed then the node to next hop link of sender is declared as the misbehaving link. We simulated the routing misbehavior detection using 2ACK scheme to test the operation scheme in terms of performance parameters.
