Method and system for correcting fabrication in a document

A fabrication correction system for correcting a fabrication in a document, comprising:

• a processor;
• and
• a memory communicatively coupled to the processor, wherein the memory stores processor instructions, which, on execution, causes the processor to:
• receive an input document from a user;
• identify a reference document based on a category of the input document, from a reference document database;
• detect fabrication indicating distortion associated with at least one of text and one or more images of the input document based on a predefined machine learning technique, by comparing one or more parameters associated with the input document with corresponding one or more parameters of the reference document;
• determine one or more fabricated regions in the input document and a type of the fabrication in each of the one or more fabricated regions, based on one or more predefined techniques, by:
• identifying one or more boundaries for multiple segmented regions in the input document using Mask Region Convolutional Neural Network (R-CNN) technique;
• generating region-proposals indicating location and boundary of fabricated regions in the input document, by applying Region Proposal Network (RPN) technique in combination with Fast R-CNN technique on each segment in the input document;
• and
• determining the type of the fabrication in each of the one or more fabricated region based on Discrete Wavelet Transform (DWT) technique, wherein the type of the fabrication comprises variation in alignment, font, wavelength, syntax pixels, ink characteristics and opacity and nature of distortion associated with the at least one of text and one or more images of the input document;
• and
• perform one or more actions in each of the one or more fabricated regions based on the type of the fabrication and the reference document, upon receiving a user input, for correcting the one or more fabricated regions.

A non-transitory computer readable medium including instruction stored thereon that when processed by at least one processor cause a fabrication correction system to perform operation comprising:

• receiving an input document from a user;
• identifying a reference document based on a category of the input document, from a reference document database;
• detecting fabrication indicating distortion associated with at least one of text and one or more images of the input document based on a predefined machine learning technique, by comparing one or more parameters associated with the input document with corresponding one or more parameters of the reference document;
• determining one or more fabricated regions in the input document and a type of the fabrication in each of the one or more fabricated regions, based on one or more predefined techniques, by:
• identifying one or more boundaries for multiple segmented regions in the input document using Mask Region Convolutional Neural Network (R-CNN) technique;
• generating region-proposals indicating location and boundary of fabricated regions in the input document, by applying Region Proposal Network (RPN) technique in combination with Fast R-CNN technique on each segment in the input document;
• and
• determining the type of the fabrication in each of the one or more fabricated region based on Discrete Wavelet Transform (DWT) technique, wherein the type of the fabrication comprises variation in alignment, font, wavelength, syntax pixels, ink characteristics and opacity and nature of distortion associated with the at least one of text and one or more images of the input document;
• and
• performing one or more actions in each of the one or more fabricated regions based on the type of the fabrication and the reference document, upon receiving a user input, for correcting the one or more fabricated regions.