Saturday, January 28, 2017

9:02 PM

Salam otomasi.,
Abre to Corazon...!!!
Camera calibration is the process of estimating intrinsic and/or extrinsic parameters. Intrinsic parameters deal with the camera's internal characteristics, such as, its focal length, skew, distortion, and image center. Extrinsic parameters describe its position and orientation in the world. Knowing intrinsic parameters is an essential first step for 3D computer vision, as it allows you to estimate the scene's structure in Euclidean space and removes lens distortion, which degrades accuracy. BoofCV provides fully automated calibration for several planar target types (see pictures above) that can be easily printed on standard sized paper.
Calibration in BoofCV is heavily influenced by Zhengyou Zhang's 1999 paper, "Flexible Camera Calibration By Viewing a Plane From Unknown Orientations". See his webpage below for the paper and theoretical information on camera calibration. A link is also provided to a popular matlab calibration toolbox. It is possible to either manually collect images and process them or to use a fully automated assisted calibration. Both approaches are described below figur 1 show about the result of image calibration.
Figure 1. Calibration database
If you want to capture image press "c" and will automatic captured 42 times. And after that press "p" to calibrate the result of image ceptured. after finished you will found intrinsic and extrinsic by yml extension to know the factor from stereo image.

For the library I used OpenCV 3.0 you can download application in this LINK. and if you want to know about how to implement stereo image to measure distance object tracking get the source code of "Image Segmentation Using HSV and Stereo Camera To Get Distance (Deep) Full Project Download"

After calibration finished you will found the intrinsic dan extrinsic like figure 2 and 3.

 Figure 1. Extrinsic factor

Figure 2. Intrinsic factor

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