CBSE Class 10th AI (Artificial Intelleigence) | 18. Introduction to Computer Vision by Abraham | Learn Smarter
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18. Introduction to Computer Vision

Computer Vision is a crucial subfield of Artificial Intelligence that allows machines to interpret and understand visual information similarly to humans. It encompasses various processes like image classification, object detection, and facial recognition, utilizing tools such as OpenCV and TensorFlow. The real-world applications of computer vision are widespread, spanning healthcare, security, and autonomous vehicles, while also presenting technical challenges and limitations.

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Sections

  • 18

    Introduction To Computer Vision

    Computer Vision is a subfield of AI that enables machines to interpret and understand visual information.

    Learning Practice

  • 18.1

    What Is Computer Vision?

    Computer Vision is a branch of AI that allows computers to interpret and understand visual data from the world.

    Learning Practice

  • 18.2

    How Computer Vision Works

    This section describes the three fundamental steps of computer vision: image acquisition, processing & analysis, and understanding or interpretation.

    Learning Practice

  • 18.2.1

    Image Acquisition

    Image acquisition is the first step in the computer vision process, involving the collection of images or videos for analysis.

    Learning Practice

  • 18.2.2

    Processing & Analysis

    This section outlines the processing and analysis involved in computer vision, detailing how raw images are transformed for interpretation.

    Learning Practice

  • 18.2.3

    Understanding Or Interpretation

    Understanding or interpretation in computer vision refers to how machines analyze and interpret visual data to make decisions.

    Learning Practice

  • 18.3

    Key Components Of Computer Vision

    This section presents the key components of computer vision, highlighting their functions and how they contribute to understanding visual data.

    Learning Practice

  • 18.4

    Tools And Libraries Used In Computer Vision

    This section discusses the essential tools and libraries utilized in computer vision, highlighting their specific use cases.

    Learning Practice

  • 18.5

    Techniques Used In Computer Vision

    This section explores key techniques used in computer vision, enhancing machines' ability to interpret visual data.

    Learning Practice

  • 18.5.1

    Edge Detection

    Edge detection is a crucial computer vision technique that identifies boundaries and transitions within images.

    Learning Practice

  • 18.5.2

    Color Detection And Filtering

    Color detection and filtering is a crucial technique in computer vision that helps machines understand visual information by extracting colors from images.

    Learning Practice

  • 18.5.3

    Feature Extraction

    Feature extraction is a crucial technique in computer vision that identifies unique patterns such as corners and textures within images for analysis.

    Learning Practice

  • 18.5.4

    Convolutional Neural Networks (Cnns)

    Convolutional Neural Networks (CNNs) are specialized deep learning models used extensively in computer vision applications to process visual data automatically.

    Learning Practice

  • 18.5.5

    Image Augmentation

    Image augmentation is a technique used in training AI models that generates multiple modified versions of the same image by applying various transformations.

    Learning Practice

  • 18.6

    Real-World Applications Of Computer Vision

    Computer vision finds extensive applications across various industries, enhancing processes and decision-making.

    Learning Practice

  • 18.7

    Advantages And Limitations

    This section outlines the advantages and limitations of computer vision, highlighting its effectiveness in automating visual tasks and the challenges it faces.

    Learning Practice

  • 18.8

    Summary

    Computer Vision enables machines to process and understand visual information through images and videos, impacting various sectors with its capabilities.

    Learning Practice

References

Chapter_18_Intro.pdf

Class Notes

Memorization

What we have learnt

  • Computer Vision enables mac...
  • It automates tasks like obj...
  • Tools like OpenCV and Tenso...

Final Test

Revision Tests