Biometric identification is the study of physiological and behavioral attributes of an individual to overcome security problems. Finger vein recognition is a biometric technique used to analyze finger vein patterns of persons for proper authentication. This paper presents a detailed review on finger vein recognition algorithms. Such tools include image acquisition, preprocessing, feature extraction and matching methods to extract and analyze object patterns. In addition, we list some novel findings after the critical comparative analysis of the highlighted techniques. The comparative studies indicate that the accuracy of finger vein identification methods is up to the mark.

A Systematic Review of Finger Vein Recognition Techniques

Objectives: Perovskite photovoltaic’s are getting to be distinctly predominant option for the conventional solar cells achieving a maximum efficiency of 22.1%. This work is concerned about the design and analyses of lead-based perovskite solar cell model with the flexible architecture of lass/FTO/PCBM/CH3NH3PbI3/PEDOT:PSS/Ag. Method/Analysis: The analysis of solar cell architecture is done using the Solar Cell Capacitance Simulator(SCAPS). It is a computer-based software tool and is well adapted for the analyses of homo and heterojunctions, multi- junctions and Schottky barrier photovoltaic devices. This software tool runs and simulates based on the Poisson’s and continuity equation of electrons and holes. For this model, it is used to optimize the various parameters such as thickness, the defect density of absorber layer, doping concentrations(ND and NA) of Electron Transport Material (ETM) and Hole Transport Material (HTM). Findings: The thickness of CH3NH3PbI3varied from 0.1μm to 0.6μm and the best results are observed at 0.3μm. The total defect density of the absorber varied from 1013 cm-3 to 1018 cm-3 and the minimum defect density of absorber layer is predicted as 1014cm-3. The ND or NA of the HTM and ETM varied from 1014 to 1019 cm-3and the PCE is maximum when ND and NA both kept at 1019cm-3. By tuning the thickness of absorber layer and doping concentrations, the predicted results are as follows; maximum power conversion efficiency(PCE)31.77%, short circuit current density (Jsc) 25.60 mA/cm2, open circuit voltage(Voc) 1.52V, fill factor(FF) 81.58%. Improvements: With this proposed simulated model, the efficiency of the perovskite solar cell reaches to the 31%, which is an improvement of 4-5%, to the previous models, with the optimization of few material parameters. Hence this simulation work will provide the handy information in fabricating perovskite solar cells to reasonably choose material parameters and to achieve the high efficiency.

Simulation and Analysis of Lead based Perovskite Solar Cell using SCAPS-1D

A review is conducted to deeply analyse and map the research landscape of current technologies in finger vein (FV) biometric authentication in medical systems into a coherent taxonomy. This research focuses on articles related to the keywords `biometrics', `finger veins' and `verification' and their variations in three major databases, namely, Web of Science, ScienceDirect and IEEE Xplore. The final set of collected articles related to FV biometric authentication systems is divided into software- and hardware-based systems. In the first category, software development attempts are described. The experiment results, frameworks, algorithms and methods that perform satisfactorily are presented. Moreover, the experiences obtained from conducting these studies are discussed. In the second category, hardware development attempts are described. The final articles are discussed from three aspects, namely, (1) number of publications, (2) problem type, proposed solutions, best results and evaluation methods in the included studies and (3) available databases containing different scientific work collected from volunteers, such as staff and students. The basic characteristics of this emerging field are identified from the following aspects: motivations of using FV biometric technology in authentication systems, open challenges that impede the technology's utility, authors' recommendations and future research prospects. A new solution is proposed to address several issues, such as leakage of biometrics that leads to serious risks due to the use of stolen FV templates and various spoofing and brute-force attacks in decentralised network architectures in medical systems, including access points and various database nodes without a central point. This work contributes to literature by providing a detailed review of feasible alternatives and research gaps, thereby enabling researchers and developers to develop FV biometric authentication medical systems further. Insights into the importance of such a technology and its integration into different medical applications and fields are also provided.

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Finger Vein Biometrics: Taxonomy Analysis, Open Challenges, Future Directions, and Recommended Solution for Decentralised Network Architectures

Recent advancements in finger vein recognition technology: Methodology, challenges and opportunities

Biometrics trait using finger-vein has attracted numerous attention from researchers all over the world since the last decade. Various approaches have been proposed in regard to improving the accuracy of identification result. This paper discusses on the approaches taken from other researches on preprocessing, feature extraction and classification stage specifically for recognizing individual identity. The strengths and weaknesses of these approaches are critically reviewed. The classification approach using machine learning method is highlighted to determine the future direction and to fill the research gap in this field.

A Review of Finger-Vein Biometrics Identification Approaches

Automatic data capturing system provides an alternative and effective way of data collection instead of manual data collection in the laboratory, especially for experiments that need to be carried out for a long period of time. It is able to solve common mistakes made by humans, like misreading or mistyping data. Thus, a new smart data recognition system for a seven segment LED display is developed to sort the whole process of data collection to become more systematic and accurate. An image is captured and saved automatically in an image file, and then it is processed through MATLAB software to identify the digits displayed on the LED display. Once the image is pre-processed, analyzed, and recognized, the final output values obtained are transferred to an existing Excel file for further process according to the user’s requirement. From the results obtained, it was proven that binary thresholding is the best pre-processing method and the brightness of the image should be set to ‘0’ for better recognition output.

https://www.ommegaonline.org/articles/publishimages/17207-Automatic- Data- Capturing -System.pdf

K. Syazana-Itqan

Papers

A Review of Finger-Vein Biometrics Identification Approaches

Automatic Data Capturing System for Seven Segment LED Display