Main Content

Image Processing and Computer Vision

Acquire, process, and analyze images and video for algorithm development and system design

With image processing and computer vision products from MathWorks®, you can perform end-to-end processing workflows from data acquisition and preprocessing, to enhancement and analysis, through deployment onto embedded vision systems.

These products enable a large variety of workflows for image, video, point cloud, lidar, and hyperspectral data. Using these products, you can:

  • Interactively visualize, explore, label, and process data using apps.

  • Enhance and analyze data algorithmically.

  • Perform semantic segmentation, object detection, classification, and image-to-image translation using deep learning.

  • Interface with hardware for image acquisition, algorithm acceleration, desktop prototyping, and embedded vision system deployment.


Label and Preprocess Data

  • Choose an App to Label Ground Truth Data (Computer Vision Toolbox)
    Decide which app to use to label ground truth data: Image Labeler, Video Labeler, Ground Truth Labeler, Lidar Labeler, Signal Labeler, or Medical Image Labeler.
  • Get Started with Image Preprocessing and Augmentation for Deep Learning (Image Processing Toolbox)
    Preprocess data for deep learning applications with deterministic operations such as resizing, or augment training data with randomized operations such as random cropping.
  • Medical Image Preprocessing (Medical Imaging Toolbox)
    Learn common preprocessing steps used in medical image analysis workflows.
  • Choose Image Registration Technique (Image Processing Toolbox)
    Choose from four approaches to image registration: the Registration Estimator app, intensity-based automatic image registration, control point registration, and automated feature matching.

Detect Objects and Features

Segment Images

Enhance Images

  • Contrast Enhancement Techniques (Image Processing Toolbox)
    Adjust the contrast of grayscale and color images using intensity value mapping, histogram equalization, and contrast-limited adaptive histogram equalization.
  • Noise Removal (Image Processing Toolbox)
    Remove image noise by using techniques such as averaging filtering, median filtering, and adaptive filtering based on local image variance.

Perform Simultaneous Localization and Mapping

Acquire and Calibrate Data

Deploy on Hardware