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Open Source Computer Vision Library
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Image sharpness, as well as brightness, are a critical parameter for accuracte camera calibration. For accessing these parameters for filtering out problematic calibraiton images, this method calculates edge profiles by traveling from black to white chessboard cell centers. Based on this, the number of pixels is calculated required to transit from black to white. This width of the transition area is a good indication of how sharp the chessboard is imaged and should be below ~3.0 pixels. Based on this also motion blur can be detectd by comparing sharpness in vertical and horizontal direction. All unsharp images should be excluded from calibration as they will corrupt the calibration result. The same is true for overexposued images due to a none-linear sensor response. This can be detected by looking at the average cell brightness of the detected chessboard. |
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OpenCV: Open Source Computer Vision Library
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