  In todays world, where the need for security is paramount and biometric
access control systems are gaining mass acceptance due to their increased
reliability, research in this area is quite relevant. Also with the advent of
IOT devices and increased community support for cheap and small computers like
Raspberry Pi its convenient than ever to design a complete standalone system
for any purpose. This paper proposes a Facial Biometric System built on the
client-server paradigm using Raspberry Pi 3 model B running a novel local
descriptor based parallel algorithm. This paper also proposes an extended
version of Local Gradient Hexa Pattern with improved accuracy. The proposed
extended version of LGHP improved performance as shown in performance analysis.
Extended LGHP shows improvement over other state-of-the-art descriptors namely
LDP, LTrP, MLBP and LVP on the most challenging benchmark facial image
databases, i.e. Cropped Extended Yale-B, CMU-PIE, color-FERET, LFW, and
Ghallager database. Proposed system is also compared with various patents
having similar system design and intent to emphasize the difference and novelty
of the system proposed.
