计算机视觉在目标检测中的应用研究

Xiang Wei, Youli Ren, Mian Huang
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引用次数: 0

摘要

目标检测是机器视觉领域的研究热点。在现代技术的创新和发展中,机器学习、模式识别、图像处理等多学科知识的融合可以有效地解决图像问题。在计算机视觉和数字图像处理技术的发展创新中,目标检测的理论研究和实际应用都取得了优异的成果,虽然还有很多问题需要解决,但是很多新技术新方法还有待开发,因此各国学者逐渐加强科研力度,纷纷提出适应性强、精度高、鲁棒性好的技术。本文在了解目标检测研究现状的基础上,根据图像处理的基本理论,分析了计算机视觉在目标检测中的应用。最后的实验结果表明,阴影检测、图像增强和滤波等方法可以有效地提高应用效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on computer vision in object detection
Object detection is a hot topic in the field of machine vision. In the innovation and development of modern technology, the integration of machine learning, pattern recognition, image processing and other multidisciplinary knowledge can effectively solve the image problem. In computer vision and digital image processing technology in the development of innovation, target detection theory research and practical application has achieved excellent results, although there are many problems need to solve, but a lot of new technology and new method has yet to be developed, so countries scholars gradually strengthen the scientific research strength, strong adaptability are put forword technique, high precision and good robustness. In this paper, based on the understanding of the research status of object detection, according to the basic theory of image processing, the application of computer vision in object detection is analyzed. The final experimental results show that shadow detection, image enhancement and filtering methods can effectively improve the application effect.
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