Structural Similarity Index Measure Based Signature Verification Using Python

This paper presents a method for digital signature verification utilizing a combination of optical character recognition (OCR) and string similarity metrics, implemented in Python. The proposed method involves preprocessing input images, extracting text, and comparing the text for similarity using the SequenceMatcher algorithm. Additionally, the Structural Similarity Index (SSIM) is employed to assess the visual similarity between the images. This paper presents a method for signature verification without delving much into machine learning or deep learning. Experimental results demonstrate the effectiveness of this approach in verifying digital signatures, offering a robust solution for enhancing security in electronic documents.