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MTESSERACT: An Application for Form Recognition in Courier Services

Despite the fact that there are various electronic alternatives to utilize and submit data, some people choose to use handwritten forms in systems like courier services. Manually entering data from handwritten forms into a system is time-consuming and error-prone. To prevent this scenario, the suggested method extracts text from handwritten forms and saves the collected data in a CSV file. This technique eliminates unnecessary work delays and makes it less prone to errors. This project applies segmentation techniques to images of handwritten forms and then uses modified tesseract functions on this segmented data to extract text from the supplied image. Formatted input aids in the achievement of better outcomes through segmentation. Pytesseract, an OCR tool, is implemented in text extraction. The main part of this proposed system is text extraction from the uploaded image, first segmenting this image and then converting it to digital text. This project will recognize the text from the handwritten form provided as input in Tesseract and try to save it to the system as a CSV file. This makes storing the data in the system automatically. This proposed system requires users to submit data in a specific format via the form provided.