Image-processing algorithms realized by discrete-time cellular neural networks and their circuit implementations

被引:51
作者
Chen, Hsin-Chieh [1 ]
Hung, Yung-Ching [1 ]
Chen, Chang-Kuo [1 ]
Liao, Teh-Lu [1 ]
Chen, Chun-Kuo [1 ]
机构
[1] Natl Cheng Kung Univ, Dept Engn Sci, Tainan 701, Taiwan
关键词
D O I
10.1016/j.chaos.2005.08.067
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In this study, eight image tasks: connected component detection (CCD) with down, right, +45 degrees and -45 degrees directions, edge detection, shadow projection with left and right directions and point removal are analyzed. These tasks are solved using the binary input and binary output discrete-time cellular neural networks (DTCNNs) associated with suitable templates. Furthermore, the behavior of the DTCNNs can be realized using Boolean functions, and the corresponding equivalent logic circuits are derived. An 8 x 8 DTCNNs-based image-processing chip is implemented by the FPGA technology. A simulation of the chip developed for the CCD task is also presented. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1100 / 1108
页数:9
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