Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (34)
  • Open Access

    ABSTRACT

    Iris Biometrics Recognition Application in Security Management

    S.S. Chowhan1, G.N. Shinde2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.6, No.1, pp. 1-12, 2008, DOI:10.3970/icces.2008.006.001

    Abstract Authentication plays a very critical role in security-related applications like e-commerce. There are a number of methods and techniques for accomplishing this key process. Biometrics is gaining increasing attention in these days. Security systems, having realized the value of biometrics, use biometrics for two basic purposes: to verify or identify users. The use of fingerprints, facial characteristics and other biometrics for identification is becoming more common. This paper overview best of Biometric application for security management. The acquisition of biometric data introduces human research and privacy concerns that must be addressed by the organizations. This paper focus Iris is the… More >

  • Open Access

    ABSTRACT

    Evaluation of Statistical Feature Encoding Techniques on Iris Images

    Chowhan S.S.1, G.N. Shinde2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.9, No.1, pp. 67-74, 2009, DOI:10.3970/icces.2009.009.067

    Abstract Feature selection, often used as a pre-processing step to machine learning, is designed to reduce dimensionality, eliminate irrelevant data and improve accuracy. Iris Basis is our first attempt to reduce the dimensionality of the problem while focusing only on parts of the scene that effectively identify the individual. Independent Component Analysis (ICA) is to extract iris feature to recognize iris pattern. Principal Component Analysis (PCA) is a dimension-reduction tool that can be used to reduce a large set of variables to a small set that still contains most of the information in the large set. Image quality is very important… More >

  • Open Access

    ARTICLE

    An Ensemble Based Hand Vein Pattern Authentication System

    M. Rajalakshmi*

    CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.2, pp. 209-220, 2018, DOI:10.3970/cmes.2018.114.209

    Abstract Amongst several biometric traits, Vein pattern biometric has drawn much attention among researchers and diverse users. It gains its importance due to its difficulty in reproduction and inherent security advantages. Many research papers have dealt with the topic of new generation biometric solutions such as iris and vein biometrics. However, most implementations have been based on small datasets due to the difficulties in obtaining samples. In this paper, a deeper study has been conducted on previously suggested methods based on Convolutional Neural Networks (CNN) using a larger dataset. Also, modifications are suggested for implementation using ensemble methods. Ensembles were used… More >

  • Open Access

    ARTICLE

    A Lightweight Three-Factor User Authentication Protocol for the Information Perception of IoT

    Liang Kou1, Yiqi Shi2, Liguo Zhang1, Duo Liu1,*, Qing Yang3

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 545-565, 2019, DOI:10.32604/cmc.2019.03760

    Abstract With the development of computer hardware technology and network technology, the Internet of Things as the extension and expansion of traditional computing network has played an increasingly important role in all professions and trades and has had a tremendous impact on people lifestyle. The information perception of the Internet of Things plays a key role as a link between the computer world and the real world. However, there are potential security threats in the Perceptual Layer Network applied for information perception because Perceptual Layer Network consists of a large number of sensor nodes with weak computing power, limited power supply,… More >

Displaying 31-40 on page 4 of 34. Per Page