Abstract
Signature verification plays a crucial role in biometric authentication systems. Traditional local texture descriptors such as Local Binary Pattern (LBP), Local Directional Pattern (LDP), and Local Tetra Pattern (LTrP) exhibit limitations in capturing detailed gradient variations in signature strokes. This paper proposes a novel Local Gradient Hexa Pattern (LGHP) descriptor for robust feature extraction in offline signature verification. The proposed method encodes gradient magnitude and directional information into a six-pattern structure, enhancing discrimination capability. Experimental evaluation is performed on standard signature datasets using a Minimum Distance Classifier. Performance comparison demonstrates that the proposed LGHP achieves improved verification accuracy and reduced false acceptance rate compared to existing descriptors. The results confirm the effectiveness and robustness of the proposed approach for biometric authentication systems.
Keywords
Signature Verification, Local Binary Pattern (LBP), Local Directional Pattern (LDP) Local Gradient Hexa Pattern (LGHP), Forgery Detection.
Citations
IRE Journals:
Alapati Rakshitha, Dr. Atluri Sri Krishna, Maddineni Sravani, Annavarapu MohanKrishna, Arumalla Somasekara Panduranga Vara Prasadad "Local Gradient Hexa Pattern: A Descriptor for Signature Verification" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 298-305 https://doi.org/10.64388/IREV9I9-1714833
IEEE:
Alapati Rakshitha, Dr. Atluri Sri Krishna, Maddineni Sravani, Annavarapu MohanKrishna, Arumalla Somasekara Panduranga Vara Prasadad
"Local Gradient Hexa Pattern: A Descriptor for Signature Verification" Iconic Research And Engineering Journals, 9(9) https://doi.org/10.64388/IREV9I9-1714833
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