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		<datestamp>2026-01-01 </datestamp>
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			<dc:title><![CDATA[Developing a Web Platform to Extract Information from Receipt Images]]></dc:title>
			<dc:creator>DEMİRHAN*,Barış</dc:creator>
			<dc:creator>KUTLU,Yakup</dc:creator>
			<dc:description><![CDATA[Data extracted from receipts are necessary for various applications in many industries, and this extraction process can be simplified through pre-trained deep learning models. However, high-quality receipt images are essential for algorithms to produce accurate models. This paper focuses on the techniques to improve the image preprocessing process and the information extraction methods applied in Turkish and English and create a web-based receipt scanning and data management system. Optical Character Recognition (OCR) technology is a system that provides a full alphanumeric recognition of printed or handwritten characters from images. Initially, OpenCV has been used to detect the bill or invoice and filter out the unnecessary noise from the image. Then the intermediate image is passed for further processing using the Tesseract OCR engine, which is an optical character recognition engine. This application is built upon a Flask backend, a responsive HTML/CSS/JavaScript frontend, and a SQLite database, offering capabilities including single and batch receipt scanning, editable JSON-based data review by both using regex and AI parser, persistent storage across two language-specific database tables, Excel export, and downloadable output bundles including raw OCR text and structured JSON files. Our methodology and system prove to be highly accurate while tested on a variety of input images of bills and invoices. The architecture is modular and extensible, making it suitable as a foundation for larger-scale document digitization workflows.]]></dc:description>
			<dc:date>2026-01-01</dc:date>
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