The article provides a detailed walkthrough of building an automated Signature Recognition system using machine learning and computer vision, covering everything from data collection to deployment. Th
e system uses SVM classification with HOG features to distinguish between genuine and forged signatures, with practical applications in banking, legal, and educational sectors.
Reasons to Read -- Learn:
how to build a complete end-to-end signature verification system using computer vision and machine learning, with detailed code examples for each implementation step.
practical techniques for image preprocessing and feature extraction using HOG (Histogram of Oriented Gradients), which can be applied to various computer vision projects beyond signature recognition.
how to deploy a machine learning model as a Flask API service, including handling image uploads and returning verification results in a production environment.
publisher: @bhatadithya54764118
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