Scale-Space Feature Detection for Close Range Camera Calibration

Imaging systems for computer vision play an important role in today´s world, with applications ranging from automated assembly and tolerance analysis, to spacecraft guidance and control. The accuracy of many of these systems relies heavily upon calibration of the vision system, and although many algorithms and techniques exist for camera calibration, most are designed for large-scene applications where multiple objects may be imaged and considered in focus simultaneously. Close-range camera systems, on the other hand, typically have a relatively narrow depth of field in which an object appears focussed. World features outside this depth of field are blurred, and so a method is desired to reliably extract information from the close-range scene even when satisfactory focus is not achieved throughout an entire image. This paper presents initial results from implementation of a discrete scale-space edge detection method, applied to feature extraction from a calibration target.