website development
Budget: ₹1,500 – ₹12,500 INR
The main objective is to recognize handwritten documents, which includes characters, words, lines, paragraphs etc. There is extensive work in the field of handwriting recognition, and a number of reviews exist. Several approaches have been used for online and offline handwriting recognition fields, such as statistical methods, structural methods, neural networks and syntactic methods. Some recognition system may identify strokes, others apply recognition on a single character or entire words. In our approach we will be implementing the offline handwriting recognition system using multi-dimensional recurrent neural network, Connectionist Temporal Classification algorithm and other related techniques.
The handwriting recognition system can be useful in various cases such as-
Healthcare and pharmaceuticals
Patient prescription digitization is a major pain point in healthcare/pharmaceutical industry. For example, Roche is handling millions of petabytes of medical PDFs daily. Another area where handwritten text detection has key impact is patient enrolment and form digitization. By adding handwriting recognition to their toolkit of services, hospitals/pharmaceuticals can significantly improve user experience
Insurance
A large insurance industry receives more than 20 million documents a day and a delay in processing the claim can impact the company terribly. The claims document can contain various different handwriting styles and pure manual automation of processing claims is going to completely slow down the pipeline.
Banking
People write cheques on a regular basis and cheques still play a major role in most non-cash transactions. In many developing countries, the present cheque processing procedure requires a bank employee to read and manually enter the information present on a cheque and also verify the entries like signature and date. As a large number of cheques have to be processed every day in a bank a handwriting text recognition system can save costs and hours of human work
The aim is to deliver a system which can prove to be helpful in the mentioned industries.
The handwriting recognition system can be useful in various cases such as-
Healthcare and pharmaceuticals
Patient prescription digitization is a major pain point in healthcare/pharmaceutical industry. For example, Roche is handling millions of petabytes of medical PDFs daily. Another area where handwritten text detection has key impact is patient enrolment and form digitization. By adding handwriting recognition to their toolkit of services, hospitals/pharmaceuticals can significantly improve user experience
Insurance
A large insurance industry receives more than 20 million documents a day and a delay in processing the claim can impact the company terribly. The claims document can contain various different handwriting styles and pure manual automation of processing claims is going to completely slow down the pipeline.
Banking
People write cheques on a regular basis and cheques still play a major role in most non-cash transactions. In many developing countries, the present cheque processing procedure requires a bank employee to read and manually enter the information present on a cheque and also verify the entries like signature and date. As a large number of cheques have to be processed every day in a bank a handwriting text recognition system can save costs and hours of human work
The aim is to deliver a system which can prove to be helpful in the mentioned industries.