Fast object segmentation in textured backgrouds

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.