Signature Verification Using Python

Signature Verification using Python is a smart way to authenticate handwritten signatures by comparing them digitally. The system checks whether a given signature matches a stored one, identifying it as genuine or forged.

Using libraries like OpenCV, the process begins with image preprocessing (grayscale conversion, thresholding, contour detection) to extract important signature features. These features include shape, stroke direction, and texture.

For classification, machine learning models like SVM or KNN are used, or advanced systems can employ Convolutional Neural Networks (CNNs) with libraries such as TensorFlow or PyTorch.

This technology is useful in banking, document verification, and legal sectors, where security and accuracy are critical. Signature verification systems reduce human error and allow for fast, automated processing.

Python’s flexibility and rich ecosystem make it ideal for building powerful signature verification applications, even with limited hardware and resources.