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Handbook Of Biometrics

Power components, power factors, and pollution factor are defined according to the IEEE standard 1459-2000 based on the fast Fourier transform (FFT). However, the FFT in the presence of nonstationary power quality (PQ) disturbances results in inaccurate values due to its sensitivity to the spectral leakage problem. In this paper, a new perspective for the IEEE standard 1459-2000 definitions is introduced using the stationary wavelet transform (SWT). As a time-frequency transform, the SWT can provide variable frequency resolution while preserving time information without spectral leakage as the FFT. Moreover, unlike other time-frequency transforms, such as discrete wavelet transform (DWT), SWT possesses the time-invariance property that keeps the time and frequency characteristics throughout all of the decomposition levels. Results of different case studies including stationary, nonstationary of synthetic, and real PQ disturbances proves the effectiveness of applying the SWT over FFT or DWT.

A New Perspective for the IEEE Standard 1459-2000 Via Stationary Wavelet Transform in the Presence of Nonstationary Power Quality Disturbance

Biometric systems are used for the verification and identification of individuals using their physiological or behavioral features. These features can be categorized into unimodal and multimodal systems, in which the former have several deficiencies that reduce the accuracy of the system, such as noisy data, inter-class similarity, intra-class variation, spoofing, and non-universality. However, multimodal biometric sensing and processing systems, which make use of the detection and processing of two or more behavioral or physiological traits, have proved to improve the success rate of identification and verification significantly. This paper provides a detailed survey of the various unimodal and multimodal biometric sensing types providing their strengths and weaknesses. It discusses the stages involved in the biometric system recognition process and further discusses multimodal systems in terms of their architecture, mode of operation, and algorithms used to develop the systems. It also touches on levels and methods of fusion involved in biometric systems and gives researchers in this area a better understanding of multimodal biometric sensing and processing systems and research trends in this area. It furthermore gives room for research on how to find solutions to issues on various unimodal biometric systems.

Unimodal and Multimodal Biometric Sensing Systems: A Review

The past decade has seen the emergence of Vehicular Clouds as a topic of research in its own right. Vehicular clouds were inspired by the reality of present-day vehicles featuring an impressive array of on-board compute, storage and sensing capabilities and by the insight that these on-board capabilities are a vast untapped resource that, at the moment, is wasted. Harvesting these vehicular resources and putting them to work in a meaningful and productive way promises to have a significant and lasting societal impact. One of the defining ways in which vehicular clouds differ from conventional clouds is resource volatility. As vehicles enter and leave the cloud, new compute resources become available while others depart, creating a volatile environment where reasoning about fundamental performance metrics becomes very challenging. Given that vehicular clouds and their numerous variants have becomes a very active field of research, this seems to be a good moment to survey the state of the art of vehicular cloud research. In this survey, we adopt an inclusive rather than an exclusive definition of various flavors of vehicular clouds. Vehicular clouds, in their many incarnations, have a huge array of potential applications. In order to bring this potential to fruition, significant research challenges have to be overcome. With this in mind, this survey identifies promising applications and draws attention to a number of research challenges facing the vehicular clouds community at large.

A Survey of Vehicular Cloud Research: Trends, Applications and Challenges

The events that took place in the year 2020 have shown us that society is still fragile and that it is exposed to events that rapidly change the paradigms that govern it. This has been shown by a pandemic like Coronavirus disease 2019; this global emergency has changed the way people interact, communicate, study, or work. In short, the way in which society carries out all activities has changed. This includes education, which has bet on the use of information and communication technologies to reach students. An example of the aforementioned is the use of learning management systems, which have become ideal environments for resource management and the development of activities. This work proposes the integration of technologies, such as artificial intelligence and data analysis, with learning management systems in order to improve learning. This objective is outlined in a new normality that seeks robust educational models, where certain activities are carried out in an online mode, surrounded by technologies that allow students to have virtual assistants to guide them in their learning.

https://www.mdpi.com/2076-3417/10/15/5371/pdf

Improvement of an Online Education Model with the Integration of Machine Learning and Data Analysis in an LMS

An Optimal (k,n)Visual Secret Sharing Scheme for Information Security

Biometrics is playing an important role for person recognition. The Biometrics identification of an individual is can be done by physiological or behavioral characteristics; where the palm print of an individual can be captured by using sensors and is one of among physiological characteristics of an individual. Palm print is a unique and reliable biometric characteristic with high usability. A palm print refers to an image acquired of the palm region of the hand. The biometric use of palm prints uses ridge patterns to identify an individual. Palm print recognition system is most promising to recognize an individual based on statistical properties of palm print image. It is rich in its features: principal lines, wrinkles, ridges, singular points and minutiae points. This paper proposes a Biometric Palm print lines extraction using image processing morphological operation. The proposed work discusses the significance; since both the palm print and hand shape images are proposed to extract from the single hand image acquired from a sensor. The basic statistical properties can be computed and are useful for biometric recognition of individual. This result and analysis will result into Total Success Rate (TSR) of experiment is 100%. This paper discusses proposed work for biometric recognition of individual by using basic statistical properties of palm print image. The experiment is carried out by using MATLAB software image processing toolbox.

/pdf/biometric-palm-prints-feature-matching-for-person-mx4sc7155p.pdf

Biometric Palm Prints Feature Matching for Person Identification

Big Data refers to large amount of data sets whose size is growing at a vast speed making it difficult to handle such large amount of data using traditional software tools available. This paper reviews the big data its back ground. First introduce general definition of big data and review on five phases of the value chain of big data (Components) such as, the quantity of data (Volume), the rate of data generation and transmission (Velocity), the types of structured, semi-structured data and unstructured data (Variety), the important results from the filtered data (Value) and the trust and integrity (Veracity). Then focus on classification based on five categories: Data stores, Content format, Data sources, Data processing, and Data staging. Finally examined the several representatives related to technologies, such as Hadoop, Data Center, Cloud Computing, and Internet of Things (IoT). These considerations aim to provide a complete overview and a big-picture to readers of this exciting area.

A review of big data environment and its related technologies

Detection of vehicles is the most imperative domain in recent years. It performs vital role in civilian and military application, vehicle tracking is one of the major application in defense sector. Traffic planning, city planning, traffic surveillance and control are the fundamental application in civilian sector. This research paper introduces morphological techniques for video vehicle detection which are based on Morphological approach. Literature survey presents recent work on vehicle detection techniques on vision based vehicle detection using sensors. Tracking the vehicle motion and recognize their features has been rising research area in the field of computer vision and image processing. Analysis of traffic images perform following steps: • Fragmentation of frames • Morphological operation on frames • Vehicle counting.

Morphology based moving vehicle detection

Biometrics refers to the identification of humans by their characteristics or traits. It is the science and technology of measuring and analyzing biological data. Biometric identifiers are often categorized as physiological or behavioral characteristics; among the features measured akin to face, fingerprints, hand geometry, handwriting, palm vein, iris, retinal, and voice etc. This paper discusses about palm vein biometric systems. The system is superior because it provides a nontransferable means of identifying people. The vein patterns are not easily spoofed, observed, damaged, obscured or changed. It is perceived as secure and integrated with "aliveness" detection. Palm vein authentication has a high level of authentication accuracy due to the uniqueness and complexity of vein patterns of the palm. The biometric data is based on human vein characteristics that stay constant throughout one's lifetime. A paper discusses about a palm vein technology, which gains much of the advantages over the traditional biometrics. The research states that human vascular structure is individually distinct. Even identical twins have different and distinct vascular patterns. The paper discusses about vein pattern recognition, imaging principles and image databases.

Vikas T. Humbe

Papers

An Optimal (k,n)Visual Secret Sharing Scheme for Information Security

Biometric Palm Prints Feature Matching for Person Identification

A review of big data environment and its related technologies

Morphology based moving vehicle detection

Review of Biometrics: Palm Vein Recognition System