Digitization of Data from Invoice using OCR
Venkata Naga Sai Rakesh Kamisetty, Bodapati Sohan Chidvilas, S. Revathy, P. Jeyanthi, V. Maria Anu, L. Mary Gladence
Abstract
Optical Character Recognition (OCR) is a predominant aspect to transmute scanned images and other visuals into text. Computer vision technology is extrapolated onto the system to enhance the text inside the digitized image. This preliminary provisional setup holds the invoice's information and converts it into JSON and CSV configurations. This model can be helpful in divination based on knowledge engineering and qualitative analysis in the nearing future. The existing system contains data extraction and nothing more. In a paramount manner, image pre-processing techniques like black and white, inverted, noise removal, grayscale, thick font, and canny are applied to escalate the quality of the picture. With the enhanced image, more OpenCV procedures are carried through. In the very next step, three different OCRs are used: Keras OCR, Easy OCR, and Tesseract OCR, out of which Tesseract OCR gives the precise result. After the initial steps, the undesirable symbols (/t, /n) are cleared to get the escalated text as an output. Eventually, a unique work that is highly accurate in giving JSON and CSV formats is developed.Impact statement— In our protrude, a front-end android app is developed which takes input from the user and stores the output onto the database. The JSON and CSV files can be viewed through an app by the end.