Image evaluation method with optoelectronic preprocessing

TLDR: In this paper, a contour sensor with a narrow gap is proposed for image contour detection in the presence of various image defects and a strongly structured background, with the aid of statistical analysis of metallurgical structures.

Abstract: The information which is relevant for image analysis and image classification is essentially contained in the image contours. Conventional methods scan the entire image using a television camera in a fixed raster and transmit the entire image information for processing into a computer. The contour sensor described in the application carries out a two-dimensional correlation with a narrow gap, and calculates the tangential component of the correlation gradient (Figure 1) during rotation of the gap. The gap detects very many adjacent pixels for every possible contour direction, and thus largely suppresses interference points in the image and the local noise caused by inhomogeneities in optoelectronic transducers. Contour detection in the presence of various image defects and a strongly structured background have been demonstrated with the aid of statistical analysis of metallurgical structures, the control of manufacturing robots in tracing object edges, automatic weld examination, and the evaluation of aerial photographs.