Composite morphological functions for DT-CNNs
Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications - Trang 587-594
Tóm tắt
Mathematical morphology is a powerful means to specify image manipulations; discrete-time cellular neural networks (DT-CNN) is the fast realization. The attractive combination has been sufficiently shown for simple problems but tends to fail in efficiency for more complex ones. The paper introduces a complement and argument swap (CAS) equivalence that allows to solve an image processing problem through a small library of representative efficient designs.
Từ khóa
#Robustness #Morphology #Image processing #Libraries #Content addressable storage #Data mining #Cellular neural networks #Joining processes #Design methodology #Process designTài liệu tham khảo
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