AI Fundamentals of Computer vision

Introduction to computer vision

Digital Marketing Academy


Introduction to computer vision


image acquisition and analysis


image processing and analysis


deep learning for computer vision


deep learning for computer vision

What is Computer Vision? Digital Marketing Academy

Computer vision is a field of artificial intelligence that deals with enabling computers to understand and interpret the visual world. It involves teaching machines to process, analyze, and understand images and videos. In essence, computer vision aims to give computers the ability to “see” and make sense of visual information, similar to how humans do.

Applications of Computer Vision

Computer vision has a wide range of applications across various industries:

  • Image and Video Analysis:
    • Object detection and recognition (e.g., facial recognition, vehicle detection)
    • Image classification (e.g., categorizing images into different classes)
    • Image segmentation (e.g., isolating specific objects or regions in an image)
  • Healthcare:
    • Medical image analysis (e.g., diagnosing diseases from X-rays, MRIs)
    • Surgical assistance
    • Patient monitoring
  • Autonomous Systems:
    • Self-driving cars
    • Robotics
    • Drones
  • Retail:
    • Product tracking
    • Customer behavior analysis
    • Visual search
  • Security:
    • Surveillance systems
    • Facial recognition for access control
    • License plate recognition

Basic Components of a Computer Vision System

A typical computer vision system consists of the following components:

  1. Image Acquisition:
    • Capturing images or videos using cameras, scanners, or other input devices.
  2. Preprocessing:
    • Enhancing image quality by removing noise, adjusting contrast, and performing other transformations.
  3. Feature Extraction:
    • Identifying and extracting relevant features from the image, such as edges, corners, textures, or colors.
  4. Feature Description:
    • Representing extracted features in a numerical form that can be processed by algorithms.
  5. Object Detection and Recognition:
    • Locating and identifying objects or patterns within the image.
  6. Scene Understanding:
    • Interpreting the overall content and context of the image or video.
  7. Decision Making:
    • Using the extracted information to make decisions or perform actions.

These components work together to enable computers to understand and interpret visual information effectively.