Research on Core Algorithms of Desktop Scanning Platform

With the in-depth advancement of informatization and digitalization, the de-mand for rapid and precise scanning of paper documents in various industries is increasing day by day. Traditional scanning devices have become difficult to meet modern demands in terms of efficiency, accuracy and ease of use. This pa-per introduces the design and implementation of an artificial intelligence-based desktop scanning platform, which utilizes the powerful machine vision system OpenCV and combines advanced image recognition, enhancement and correc-tion algorithms. Using a personal computer as the hardware platform, the images of paper documents are collected through an external camera. The OpenCV im-age processing technology is utilized for image segmentation, color correction and shape correction, and ultimately high-quality JPG and PDF format docu-ments are generated. The system also supports contactless scanning and OCR preprocessing, making it suitable for long-distance text recognition and the dig-itization of precious documents. The research adopts the joint programming of C and OpenCV, designs a user-friendly interactive interface, and realizes automat-ic correction through edge detection and 3D reconstruction technology. The test results show that the system performs outstandingly in terms of scanning accu-racy, efficiency and stability. It is suitable for personal and professional use, es-pecially for the needs of enterprises, educational institutions and government departments.