Research on Core Algorithms of Desktop Scanning Platform

Abstract

With the in-depth advancement of informatization and digitalization, the demand 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 paper 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 correction algorithms. Using a personal computer as the hardware platform, the images of paper documents are collected through an external camera. The OpenCV image processing technology is utilized for image segmentation, color correction and shape correction, and ultimately high-quality JPG and PDF format documents are generated. The system also supports contactless scanning and OCR preprocessing, making it suitable for long-distance text recognition and the digitization of precious documents. The research adopts the joint programming of C and OpenCV, designs a user-friendly interactive interface, and realizes automatic correction through edge detection and 3D reconstruction technology. The test results show that the system performs outstandingly in terms of scanning accuracy, efficiency and stability. It is suitable for personal and professional use, especially for the needs of enterprises, educational institutions and government departments.