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BoofCV is an open source library written from scratch for real-time computer vision. Its functionality covers a range of subjects, low-level image processing, camera calibration, feature detection/tracking, structure-from-motion, fiducial detection, and recognition. BoofCV has been released under an Apache 2.0 license for both academic and commercial use. BoofCV is organized into several packages: image processing, features, geometric vision, calibration, recognition,visualize, and IO. Image processing contains commonly used image processing functions which operate directly on pixels. Features contains feature extraction algorithms for use in higher level operations. Calibration has routines for determining the camera's intrinsic and extrinsic parameters. Recognition is for recognition and tracking complex visual objects. Geometric vision is composed of routines for processing extracted image features using 2D and 3D geometry. Visualize has routines for rendering and displaying extracted features. IO has input and output routines for different data structures.

New calibration tools in v0.39	Summary of v0.38 Release

2021-Oct: Camera Calibration Tutorial has been re-written.

2021-Mar: Stereo Cloud from Mars Perseverance Rover

2020-Dec: 3D Reconstruction on Android

2020-June: BoofCV Summary for 0.34-0.36

2020-June: PyBoof 0.36.0 released

2020-May: Tutorial for BoofCV on Raspberry PI

2020-May: Tutorial Video for Creating a Desktop Application

2020-Apr: Raspberry PI Instructions

2020-Feb: Kotlin QR Code Scanning

Current Release: v0.39 Date: October 8, 2021 Change Log Video Summary v0.34 - v0.36

Manual FAQ JavaDoc Report Bug Message Board Papers/Reports

Download Videos Applications Bounties Contribute BoofCPP

Performance Road Map Validation Users Acknowledgements

Prebuild Stand Alone Applications

Examples / Demonstrations	Example and demonstration applications
QR Code Generator	Create and print QR Codes
Square Fiducials	Binary/Image Square Fiducial Generator
Calibration Targets	Calibration Target Generator
Calibration	Camera Calibration Application
Lens Undistortion	Batch Removal of Lens Distortion
Image Downsize	Batch Image Down Sampling with minimal aliasing

Capability Summary
Image Processing	Feature	Recognition	Geometric	Integration
Image Convolution Example Image Derivatives Example Thresholding Example Binary Ops Example Color Space Example Interpolation Example Image Deformation Example Image Blur Example Enhancement Example Noise Removal Example Fourier Transform Example Wavelet Decomposition Discrete Image Pyramid Example Float Image Pyramid Example Scale Space Image Equirectangular Example Fisheye Cameras Example	Black Polygons Example Black Ellipses Example Interest Points Example Line Detection Example Motion Detection Example Binary Contours Example Polygon Fitting Example Ellipse Fitting Example Template Matching Example Interest Points Example Dense Features Example Point Tracking Example Non-max Suppression Example Dense Optical Flow Example Superpixels Example Color Segmentation Example	Color Image Lookup Example KNN Classifier Example CNN Classifiers Example Object Tracking Example Fiducials Tutorial QR Codes Tutorial	Camera Calibration Tutorial Mono Calibration Example Stereo Calibration Example Remove Distortion Example Bundle Adjustment Example 3D Stereo Cloud Example Monocular Stereo Example Uncalibrated Stereo Example Scene Reconstruction Example Video Stabilization Example Video Mosaic Example Visual Odom: Stereo Example Visual Odom: Mono Plane Example Visual Odom: RGB-D Example	Visualization Android Video Kinect Processing Python