Accurate Depth Dependent Lens Distortion Models: An Application to Planar View Scenarios
Journal of Mathematical Imaging and Vision
Automatic Radial Distortion Estimation from a Single Image
Journal of Mathematical Imaging and Vision
Corisco: Robust edgel-based orientation estimation for generic camera models
Image and Vision Computing
Demisting the Hough Transform for 3D Shape Recognition and Registration
International Journal of Computer Vision
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In this paper, we present a simple and robust method for self-correction of camera distortion using single images of scenes which contain straight lines. Since the most common distortion can be modelled as radial distortion, we illustrate the method using the Harris radial distortion model, but the method is applicable to any distortion model. The method is based on transforming the edgels of the distorted image to a 1-D angular Hough space, and optimizing the distortion correction parameters which minimize the entropy of the corresponding normalized histogram. Properly corrected imagery will have fewer curved lines, and therefore less spread in Hough space. Since the method does not rely on any image structure beyond the existence of edgels sharing some common orientations and does not use edge fitting, it is applicable to a wide variety of image types. For instance, it can be applied equally well to images of texture with weak but dominant orientations, or images with strong vanishing points. Finally, the method is performed on both synthetic and real data revealing that it is particularly robust to noise.