Computer Vision is a branch of AI that allows machines to see, interpret, and understand visual data from the world, such as images and videos.
It enables applications like object detection, image recognition, facial recognition, and autonomous vehicles, mimicking human vision capabilities.
How Computer Vision Works
- Image Acquisition: Capture images or videos from cameras or sensors.
- Preprocessing: Enhance, normalize, and filter visual data.
- Feature Extraction: Identify key patterns, edges, shapes, and textures.
- Modeling: Use machine learning or deep learning models (CNNs, Transformers) to interpret visual information.
- Output: Classify, detect, or track objects in real-time or batch processing.
Advantages of Computer Vision
- Automates visual tasks that require human inspection
- Works in real-time for surveillance and autonomous systems
- Improves accuracy in medical imaging and quality control
- Enhances safety and efficiency in industrial applications
Real-World Examples
- Autonomous vehicles: Detecting pedestrians and traffic signs
- Facial recognition: Security and identity verification
- Medical imaging: Detecting tumors or anomalies
- Retail: Visual search and inventory management
- Surveillance: Object and activity detection
Conclusion
Computer Vision transforms visual data into actionable insights. By enabling machines to “see,” it powers some of the most exciting AI applications today.
Citations
https://savanka.com/category/learn/ai-and-ml/
https://www.w3schools.com/ai/