Recognition, Object Detection, and Semantic Segmentation - MATLAB & Simulink (original) (raw)

Recognition, classification, semantic image segmentation, instance segmentation, object detection using features, and deep learning object detection using CNNs, YOLO, and SSD

Computer Vision Toolbox™ supports several approaches for image classification, object detection, semantic segmentation, instance segmentation, and recognition, including:

• Deep learning and convolutional neural networks (CNNs)
• Bag of features
• Template matching
• Blob analysis
• Viola-Jones algorithm

A CNN is a popular deep learning architecture that automatically learns useful feature representations directly from image data. Bag of features encodes image features into a compact representation suitable for image classification and image retrieval. Template matching uses a small image, or template, to find matching regions in a larger image. Blob analysis uses segmentation and blob properties to identify objects of interest. The Viola-Jones algorithm uses Haar-like features and a cascade of classifiers to identify objects, including faces, noses, and eyes. You can train this classifier to recognize other objects.

Categories

• Object Detection
  Perform classification, object detection, transfer learning using convolutional neural networks (CNNs, or ConvNets), create customized detectors
• Semantic Segmentation
  Semantic image segmentation
• Instance Segmentation
  Perform instance segmentation using pretrained deep learning networks and train networks using transfer learning on custom data
• Image Category Classification
  Create vision transformer or bag of visual words image classifier
• Automated Visual Inspection
  Automate quality control tasks using anomaly detection and localization methods
• Text Detection and Recognition
  Detect and recognize text using image feature detection and description, deep learning, and OCR
• Keypoint Detection
  Detect keypoints in objects using convolutional neural networks (CNNs)
• Video Classification
  Perform video classification and activity recognition using deep learning

Featured Examples