METHODS AND SYSTEMS FOR ADAPTIVE, TEMPLATE-INDEPENDENT HANDWRITING EXTRACTION FROM IMAGES USING MACHINE LEARNING MODELS

Abstract: methods and systems for adaptive, template-independent handwriting extraction from images using machine learning models and without manual localization or review. for example, the system may receive an input image, wherein the input image comprises native printed content and handwritten content. the system may process the input image with a model to generate an output image, wherein the output image comprises extracted handwritten content based on the native handwritten content. the system may process the output image to digitally recognize the extracted handwritten content. the system may generate a digital representation of the input image, wherein the digital representation comprises the native printed content and the digitally recognized extracted handwritten content.

Inventor(s): Houssem CHATBRI, Bethany KOK

CPC Classification: G06V40/382 (IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING)

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