This paper presents a methodology for delineating densely packed aggregate particles based on aggregate image classification. There is no earlier work on segmentation of aggregate particles has exploited these two building blocks for making robust object delineation. The proposed method has been tested experimentally for different kinds of densely packed aggregate images, which are difficult to detect by a normal edge detector. As tested, the studied algorithm can be applied into other applications too. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Wang, W. (2007). Image classification and segmentation for densely packed aggregates. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4426 LNAI, pp. 887–894). Springer Verlag. https://doi.org/10.1007/978-3-540-71701-0_99
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