Image Edge Detection Based on Swarm Intelligence Using Memristive Networks

被引:36
|
作者
Pajouhi, Zoha [1 ]
Roy, Kaushik [2 ]
机构
[1] Intel Corp, Santa Clara, CA 95054 USA
[2] Purdue Univ, W Lafayette, IN 47907 USA
关键词
AgS memristor; ant colony; elements with memory; gap-type memristor; image edge detection; image processing; memcomputing; memory; memristor model; memristors; neural computing; NP-complete; Silver memristor; stochastic processing; swarm intelligence; OPTIMIZATION; SYSTEMS; DEVICES; COLONY;
D O I
10.1109/TCAD.2017.2775227
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Recent advancements in the development of memristive devices has opened new opportunities for hardware implementation of new computing models. Researchers have shown the suitability of memristive devices for swarm intelligence algorithms to solve a maze in hardware. In this paper, we utilize swarm intelligence of memristive networks to perform image edge detection. First, we propose a hardware-friendly algorithm for image edge detection based on ant colony optimization. Second, we implement the image edge detection algorithm using memristive networks. Furthermore, we explain the impact of various parameters of the memristors on the efficacy of the implementation. Our results show 28% improvement in the energy compared to a low power CMOS hardware implementation based on stochastic circuits. Furthermore, our design occupies up to 5 x less area.
引用
收藏
页码:1774 / 1787
页数:14
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