Abstract : Computers can now analyze and comprehend visual data from the outside world because to the development of computer vision, a branch of artificial intelligence. It entails the creation of algorithms and methods to extract significant data from pictures and movies. The sophisticated open-source computer vision and machine learning software library known as OpenCV makes it simpler to work with visual data. OpenCV is an acronym for Open-Source Computer Vision Library. The goal of computer vision is to mimic the capacity of the human visual system to comprehend and interpret the visual environment. It involves activities like object detection, facial recognition, image segmentation, and more. It also incorporates image and video analysis. Numerous industries use computer vision, including autonomous vehicles, robotics, surveillance, and augmented reality. Frequently popular open-source library OpenCV offers tools, routines, pre-built algorithms, and tools for executing different computer vision tasks. Although it was initially created by Intel, the project is now community-driven. Python and other languages provide bindings for OpenCV, which is built in C++.Computers can now analyze and comprehend visual data from the outside world because to the development of computer vision, a branch of artificial intelligence. It entails the creation of algorithms and methods to extract significant data from pictures and movies. The sophisticated open-source computer vision and machine learning software library known as OpenCV makes it simpler to work with visual data. OpenCV is an acronym for Open-Source Computer Vision Library. The goal of computer vision is to mimic the capacity of the human visual system to comprehend and interpret the visual environment. tasks such as image and video analysis.
Cite : Gouri, M. H., & Kumar, M. (2023). Computer Vision With Open CV (1st ed., p. 35). Noble Science Press. https://doi.org/10.52458/9789388996747.nsp2023.eb.ch-05
References :
"Learning OpenCV 4 Computer Vision with Python 3" by Joseph Howse, Prateek Joshi, and Michael Beyeler: This book provides a comprehensive guide to computer vision using OpenCV with Python and covers various applications and techniques.
"OpenCV 3 Computer Vision Application Programming Cookbook" by Robert Laganiere: This book offers practical examples and recipes for implementing computer vision applications using OpenCV.
"OpenCV By Example" by Prateek Joshi: This book provides a hands-on approach to learning OpenCV through practical examples and projects, making it suitable for those looking to apply computer vision in real-world scenarios.
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