Signature Verification Using Local Optimal-Oriented Pattern (LOOP)

Signature verification is a challenging biometric problem due to high intra-class variation and skilled forgeries. Traditional texture-based descriptors such as Local Binary Pattern (LBP) and Local Directional Pattern (LDP) have been widely used for this task; however, their sensitivity to rotation limits robustness. This work presents an offline signature verification system based on the Local Optimal-Oriented Pattern (LOOP), which inherently embeds rotation invariance into its formulation. Experimental evaluation on genuine and forged signatures demonstrates that LOOP-based features achieve superior discrimination compared to LBP and LDP.