Extração de feições retas com precisão subpixel: estudo comparativo entre três métodos

Abstract

In the fields of Machine Vision and Photogrammetry, extracted straight lines from digital images can be used either as vector elements of a digital representation or as control entities that allow the determination of the camera interior and exterior orientation parameters. Applications related with image orientation require feature extraction with subpixel precision, to guarantee the reliability of the estimated parameters. This paper presents three approaches for straight line extraction with subpixel precision. The first approach considers the subpixel refinement based on the weighted average of subpixel positions calculated on the direction perpendicular to the segmented straight line. In the second approach, a parabolic function is adjusted to the grey level profile of neighboring pixels in a perpendicular direction to the segmented line, followed by an interpolation of this model to estimate subpixel coordinates of the line center. In the third approach, the subpixel refinement is performed with a parabolic surface adjustment to the grey level values of neighboring pixels around the segmented line. The intersection of this surface with a normal plane to the line direction generates a parabolic equation that allows estimating the subpixel coordinates of the point in the straight line, assuming that this is the critical point of this function. Three experiments with real images were made and the approach based on parabolic surface adjustment has presented better results.