OpenCV Fundamentals

OpenCV (Open Source Computer Vision Library) is a free, open-source computer vision and machine learning software library. The fundamentals of OpenCV cover the basic building blocks of computer vision, including image processing, object detection, and machine learning algorithms.

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OpenCV (Open Source Computer Vision Library) is a free, open-source computer vision and machine learning software library. The fundamentals of OpenCV cover the basic building blocks of computer vision, including image processing, object detection, and machine learning algorithms.

Some of the key concepts in OpenCV fundamentals include:

  1. Image Processing: Techniques for transforming, manipulating and analyzing digital images, including color correction, filtering, and edge detection.
  2. Object Detection: Techniques for identifying and locating objects within images, including feature extraction and matching, and Haar cascades.
  3. Machine Learning: The application of statistical models and algorithms to enable systems to improve automatically based on experience, including supervised and unsupervised learning algorithms.
  4. Computer Vision: The study of how computers can be made to interpret and understand the visual world, including image and video analysis, and scene understanding.

OpenCV provides a comprehensive set of tools and functions for these areas, making it a popular choice for computer vision and image processing applications in various industries.

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Simran Dubey

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