Abstract

Computer image processing and recognition technology is a field that covers multiple disciplines such as computer science, electronic engineering, and mathematics. It is committed to developing algorithms and technologies to process and understand digital images. In image processing, the key is to extract features from the image, which helps to understand the content of the image. The extracted features can include color, texture, shape, edges, etc. Based on the extracted features, image recognition algorithms can classify images into different categories. With powerful computing capabilities and a wide array of tools, coupled with the rapid advancement of digital image acquisition technology through long-term practice and development, image processing and recognition technology has emerged as a crucial branch of computer vision. It has progressively evolved into a pivotal tool for addressing intricate problems and enhancing quality of life. At present, image processing and recognition technology still face a series of challenges, such as target recognition in complex scenes, processing large-scale image data, and ensuring privacy protection. This article analyzes the principles of computer image processing and recognition technology and explores the optimization of this technology in specific application processes.