A One-Quadrant Discrete-Time Cellular Neural Network Architecture For Pixel-Level Snakes: B/W Processing
2005 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), VOLS 1-6, CONFERENCE PROCEEDINGS(2005)
摘要
This paper introduces a One-Quadrant Discrete-Time Cellular Neural Network architecture for the Pixel-Level Snakes, an active-contour-based technique. The motivation behind such an architecture is to have a subsequent on-chip implementation with better figures of merit, especially area consumption and processing speed. The current paper goes through the B/W operations performed in the Pixel-Level Snake algorithm.
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关键词
active contour,data mining,semiconductor device modeling,computer architecture,computer science,hardware,image processing,pixel,cellular neural networks,information technology,cellular neural network,discrete time,figure of merit,chip
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