hackformers_0coding_8
Gst Invoice Validator
Introduction
Team members:
Domain : AI / ML �Future Scope : Using decentralized principle
Problem Statement:
There is need of system to prevent businesses and individuals from using false GST numbers to evade taxes or fraudulently claim input tax credits. This is important because businesses are required to collect GST from their customers on behalf of the government, and false GST numbers can lead to a loss of revenue for the government.
Objective
The objective of extracting the GST number from the given image of a GST bill is to automate the process of identifying and extracting GST numbers from bill images. This can save time and improve accuracy, especially for businesses that deal with a high volume of bills. By developing a computer vision-based solution that can accurately recognize and extract GST numbers, we can help streamline the billing process and reduce errors. Additionally, the solution can be used to identify fraudulent bills, which can help in maintaining the integrity of the GST system. Ultimately, the objective is to create a more efficient and accurate billing system for businesses and individuals alike.
Benefits
1. Time-saving: Extracting the GST number from an image of a GST bill can save a lot of time compared to manually going through each bill and entering the information. This can be particularly useful for businesses that deal with a high volume of bills.
2 .Fraud detection: Automated extraction can help identify fraudulent bills and invoices. This can reduce the risk of paying fraudulent bills and improve the integrity of the GST system.
Scope:-
1. Image preprocessing: Before extracting the GST number, the image needs to be processed to improve the quality of the image, remove background noise, and enhance the text in the image.
2. GST number recognition: This involves developing a computer vision-based algorithm that can accurately recognize the GST number from the given image of a GST bill. Integration with existing software: The solution can be integrated with existing billing software to automate the extraction of GST numbers, eliminating the need for manual data entry.
FlowChart
Web Interface
Home Page
Output
Conclusion
The software application takes input data from invoices, purchase orders, and payment receipts to accurately calculate GST liabilities and credits, and identify errors or discrepancies in GST returns. By leveraging machine learning techniques, the application can identify patterns and anomalies in GST data, flag potential errors or discrepancies, and provide real-time feedback to businesses to help them make informed decisions. Overall, the software application will help businesses to streamline their GST calculation process, reduce manual data entry, and improve accuracy. It will provide businesses with greater visibility into their financial data and help them to make better financial decisions.