ComputerZiči
Interactive simulation of image processing, object recognition, and computer vision
Interactive Simulation
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How does computer vision work?
🖼️ Image processing
The computer vision starts with processing images through filters, improving quality and detecting key features.
Image → Previous Processing → Feature Detection →
Classification → Object Recognition
🔍 Detection of edges
Edge detection algorithms (Sobel, Canny) find object boundaries by analyzing pixel intensity changes.
Sobel: G = √(Gx² + Gy²)
Canny: Gradient → Suppression → Threshold
🎯 Object Recognition
1. Feature Extraction
Key feature detection: corners, edges, textures, colors. Used are SIFT, SURF, or deep networks.
2. Classification
Object classification based on detected features. SVM, Random Forest, or CNN are used.
3. Localization
Defining the precise location of objects in the image. Bounding boxes or segmentation are used.
🧠 Deep learning in CV
Convolutional Neural Networks (CNN)
Specialized networks for image processing use convolutional layers to detect patterns
Transfer Learning
Using pre-trained models (ResNet, VGG) for new tasks with fewer data
Object Detection
Algorithms like YOLO, R-CNN, SSD for simultaneous object detection and classification