Abstract
In applications involving visual inspection, it is often required to separate objects from background, in conditions of poor and nonuniform illumination. In such cases one has to rely on adaptive methods that learn the illumination from the given images and base the object/background decision on this information. We here present a new method for image segmentation via adaptive thresholding. The threshold surface is determined by interpolating the image gray levels at points where the gradient is high, indicating probable object edges. Several methods of data interpolation to levels given at scattered points in the image plane are discussed. One method is tested on several examples and the segmentation results are compared to previously proposed adaptive thresholding algorithms.
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