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In this paper, we deal with the problem of detecting and segmenting objects in textured darkfield digital imagery for automated visual inspection applications. The technique we will follow is based on a sequential application of local operators which serves the purpose of clustering the object and the background gray levels. This procedure can be considered as an extension of average-thresholding type techniques. This algorithm has fast implementations in general purpose image processing pipeline architectures and therefore, it is appealing to real-time computer vision applications. Computational examples showing the effectiveness of the segmentation technique will be discussed.