Facial Biometric System for Recognition using Extended LGHP Algorithm on Raspberry Pi
Soumendu Chakraborty, Satish Kumar Singh, Kush Kumar

TL;DR
This paper presents a facial biometric recognition system using an extended LGHP algorithm on Raspberry Pi, demonstrating improved accuracy and performance over existing descriptors on multiple challenging facial image datasets.
Contribution
The paper introduces an extended version of the Local Gradient Hexa Pattern (LGHP) algorithm and implements it on a Raspberry Pi-based biometric system, enhancing recognition accuracy and efficiency.
Findings
Extended LGHP outperforms LDP, LTrP, MLBP, and LVP on benchmark datasets.
System achieves higher accuracy on Yale-B, CMU-PIE, FERET, LFW, and Ghallager databases.
Proposed system is competitive with existing patents in biometric recognition.
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
