BUSINESS CONSULTING
Objective – To develop a cutting-edge AI and OCR technology-based solution for extracting information from unstructured documents, such as PDFs and images.
How We Did It- To build a state-of-the-art pipeline for contour detection and OCR technology, we used a DL model for classifying documents based on 10 categories, passed documents through an OCR library for text extraction, filtered the extracted text for desired keywords, and stored the results in a database for further processing.
Our objective was to develop a state-of-the-art pipeline for contour detection and OCR technology to streamline the document processing and information extraction process. Here’s how we did it:
- We built a pipeline for contour detection to find the edges of documents and crop them separately.
- We passed all the documents through a DL model for classifying documents based on 10 categories, such as invoices, receipts, and forms.
- After classification, we passed all the individual documents through the latest open-source OCR libraries to convert images to text, such as Tesseract, OCRopus, and GOCR.
- We filtered out the text extracted to find the desired keywords from the corpus, such as names, addresses, and amounts.
- We stored the results in the database for further processing, such as data analysis, extraction, and integration.
Our pipeline for contour detection and OCR technology is cutting-edge and can efficiently extract information from unstructured documents for enhanced decision-making and streamlined business processes.
