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Robotics & Artificial Intelligence

Explain the various applications of computer vision.

AI Concepts

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Some important applications of computer vision are:

  1. Image recognition: Computer vision algorithms can analyse and identify objects, sceneries, and patterns from an image or video. Object identification, image categorisation, facial recognition, and visual search are examples of image recognition.
  2. Object tracking: Computer vision algorithms can track and follow certain objects or subjects in real-time camera feeds or videos. This is important in applications such as surveillance, self-driving cars, and augmented reality.
  3. Image segmentation: Image segmentation is the process by which computer vision algorithms divide images into meaningful sections or segments, allowing for more detailed analysis and understanding of the visual content.
  4. Scene comprehension: Computer vision techniques allow machines to understand and interpret the context and semantics of a visual scene. This includes tasks such as scene recognition, scene comprehension and context-based image comprehension.
  5. Three-dimensional (3D) modelling: Computer vision algorithms can recreate three-dimensional models of objects or scenes from two-dimensional photographs or video recordings. This is useful in 3D mapping, virtual reality, and robotics.
  6. Visual inspection and quality control: In industries, computer vision systems are used for automated inspection, defect identification, and quality control. They can detect flaws, irregularities, or errors in products or production processes.
  7. Medical imaging: Computer vision is used for activities such as tumour identification, diagnosis, and analysis of medical scans like X-rays, CT scans, and MRIs.
  8. Robotics: Computer vision is essential in robotic systems as it allows robots to observe and interact with their surroundings. Vision-based robots can manoeuvre, grip objects, recognise objects, and work with humans.

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