Method and system for relevant data extraction from a document

A system for extracting relevant data from a document image, the system comprising:

• a processor;
• and
• a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution by the processor, cause the processor to:
• determine first positional information comprising at least one first bounding box, corresponding to at least one key from a plurality of predefined keys in the document image based on a deep learning model,
• wherein the deep learning model is trained based on user-inputted predefined mapping information for a plurality of templates, and
• wherein the first positional information is determined based on the user-inputted predefined mapping information corresponding to each of the plurality of predefined keys;
• determine second positional information comprising one or more second bounding boxes, corresponding to the at least one key from the plurality of predefined keys based on an optical character recognition (OCR) of the document image and an NLP model,
• wherein the NLP model is trained based on the plurality of templates corresponding to the plurality of predefined keys, and
• wherein the second positional information is further processed based on a plurality of pre-defined rules comprising a predefined mapping information for each of the plurality of predefined keys in each of the plurality of templates;
• determine final positional information for the at least one key based on comparison of the first positional information and the second positional information, in case a difference between the first positional information and the second positional information is minimal;
• and
• extract relevant data for the at least one key in the OCR document image based on the final positional information.

A non-transitory computer-readable medium storing computer-executable instructions for extracting relevant data from a document image, the computer-executable instructions configured for:

• determining first positional information comprising at least one first bounding box, corresponding to at least one key from a plurality of predefined keys in the document image based on a deep learning model,
• wherein the deep learning model is trained based on user-inputted predefined mapping information for a plurality of templates, and
• wherein the first positional information is determined based on the user-inputted predefined mapping information corresponding to each of the plurality of predefined keys;
• determining second positional information comprising one or more second bounding boxes, corresponding to the at least one key from the plurality of predefined keys based on an optical character recognition (OCR) of the document image and an NLP model,
• wherein the NLP model is trained based on the plurality of templates corresponding to the plurality of predefined keys, and
• wherein the second positional information is further processed based on a plurality of pre-defined rules comprising a predefined mapping information for each of the plurality of predefined keys in each of the plurality of templates;
• determining final positional information for the at least one key based on comparison of the first positional information and the second positional information, in case a difference between the first positional information and the second positional information is minimal;
• and
• extracting relevant data for the at least one key in the OCR document image based on the final positional information.