Manual

Development with BoofCV

The following manual provides an introduction to development with BoofCV. It is assumed that the reader is familiar with development in the Java programming language and the basics of computer vision. This manual primarily takes the form of tutorials. However, before going through the tutorials one should be familiar with coding standards use in BoofCV. Once these are understood one will be able to efficiently search the library or even guess the names of classes which are needed.

Click here for Coding Standards.

List of Examples and Tutorial

A few tutorials and examples are provided to provide the basic concepts of development with BoofCV.

Tutorials:

1. Quick Start
2. Images in BoofCV
3. Videos and Webcams
4. Camera Calibration (preview)
5. 3D Computer Vision (preview)

Example Code:

1. Image Filters (Derivatives)
2. Using MultiSpectral Images
3. Binary Images
4. Image Pyramid
5. Wavelet Noise Removal
6. Detecting Lines and Line Segments
7. Detecting Interest Points
8. Associate Interest Points
9. Image Stitching
10. Track Point Features
11. Computing SURF Features
12. Calibrate Monocular Camera
13. Remove Lens Distortion
14. Calibrate Stereo Camera
15. Rectify Calibrated Stereo
16. Rectify Uncalibrated Stereo
17. Compute Fundamental Matrix

Other resources:

• List of Applets

Building BoofCV

The easiest way to build the library from source is using the provided ant scripts.

1. Download source code. See the Main Page for where to download it from.
2. Run the ant script inside the boofcv/main directory.
3. Copy the BoofCV.jar from boofcv/lib.

In Linux it looks something like this:

$ cd boofcv/main/
$ ant
---- lots of text -----
    [javac] Note: Some input files use unchecked or unsafe operations.
    [javac] Note: Recompile with -Xlint:unchecked for details.
    [javac] 15 warnings

jar:
      [jar] Building jar: /home/pja/projects/boofcv/main/jar/BoofCV_IO.jar

main:
      [jar] Building jar: /home/pja/projects/boofcv/lib/BoofCV.jar

main:

BUILD SUCCESSFUL
Total time: 7 seconds