English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The rapid development in many applications for some different areas, such as public security, access control and surveillance, requires reliable and automatic personal recognition for effective security control. Traditionally, passwords (knowledge-based security) and ID cards (token-based) have been used. However, security can be easily breached when a password is divulged or a card is stolen; further, simple passwords are easy to guess and difficult passwords may be hard to recall (Kong & Zhang; 2002). At present, applications of biometrics are rapidly increasing due to inconveniences in using traditional identification method. Biometrics refers to the technologies that can automate the recognition of persons based on one or more intrinsic physical or behavioral traits. Currently, a number of biometric based technologies have been developed and hand-based person identification is one of these technologies. This technology provides a reliable, low cost and user-friendly solution for a range of access control applications (Kumar & Zhang; 2002). In contrast to other modalities, like face and iris, hand based biometric recognition offers some advantages. First, data acquisition is simple using off the shelf low-resolution cameras, and its processing is also relatively simple. Second, hand based access systems are very suitable for several usages. Finally, hand features are more stable over time and are not susceptible to major changes (Sricharan & Reddy; 2006). Some features related to a human hand are relatively invariant and distinctive to an individual. Among these features, palmprint modality has been systematically used for human recognition using the palm patterns. The rich texture information of palmprint offers one of the powerful means in personal identification (Fang & Maylor; 2004). Several studies for palmprint-based personal recognition have focused on improving the performance of palmprint images captured under visible light. However, during the past

Multimodal Biometric Person Recognition System Based on Multi-Spectral Palmprint Features Using Fusion of Wavelet Representations