A systolic array architecture for morphological operators using arbitrary structuring elements

D. Mukherjee, S. Mukhopadhyay, G. P. Biswas
{"title":"A systolic array architecture for morphological operators using arbitrary structuring elements","authors":"D. Mukherjee, S. Mukhopadhyay, G. P. Biswas","doi":"10.1145/2979779.2979796","DOIUrl":null,"url":null,"abstract":"This paper presents an 2-D systolic array architecture for an efficient implementation of gray-scale morphological dilation using arbitrary structuring element and used it to design 2-stage pipelined architecture for morphological opening. The proposed systolic array architecture processes pixels on stream that eliminates the need for buffering image data prior to processing. Additionally, unlike existing systolic array architecture, it does not necessarily adds delay element for processing pixels of an image thereby increasing the processing frame rate. The 2-stage pipelined architecture, on the other hand, provides better performance compared to naive hardware implementation to compute morphological opening. The architecture has been synthesized using Xilinx Design Suite 14.2 ISE and prototyped on Virtex 6 FPGA Board (XC6VLX240T-3FF1156) and verified using Xilinx ISIM Simulator. The architecture provides real time performance when tested for high resolution images using moderate size non-rectangular SEs and results outperforms existing systolic array implementation.","PeriodicalId":298730,"journal":{"name":"Proceedings of the International Conference on Advances in Information Communication Technology & Computing","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Advances in Information Communication Technology & Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2979779.2979796","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This paper presents an 2-D systolic array architecture for an efficient implementation of gray-scale morphological dilation using arbitrary structuring element and used it to design 2-stage pipelined architecture for morphological opening. The proposed systolic array architecture processes pixels on stream that eliminates the need for buffering image data prior to processing. Additionally, unlike existing systolic array architecture, it does not necessarily adds delay element for processing pixels of an image thereby increasing the processing frame rate. The 2-stage pipelined architecture, on the other hand, provides better performance compared to naive hardware implementation to compute morphological opening. The architecture has been synthesized using Xilinx Design Suite 14.2 ISE and prototyped on Virtex 6 FPGA Board (XC6VLX240T-3FF1156) and verified using Xilinx ISIM Simulator. The architecture provides real time performance when tested for high resolution images using moderate size non-rectangular SEs and results outperforms existing systolic array implementation.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用任意结构元素的形态运算符的收缩数组体系结构
本文提出了一种利用任意结构元素有效实现灰度形态扩张的二维收缩阵列架构,并利用该架构设计了两阶段流水化的形态开放架构。所提出的收缩阵列架构在流上处理像素,从而消除了在处理之前缓冲图像数据的需要。此外,与现有的收缩阵列结构不同,它不需要增加用于处理图像像素的延迟元素,从而提高处理帧速率。另一方面,与简单的硬件实现相比,两阶段的流水线架构在计算形态打开方面提供了更好的性能。该架构使用Xilinx Design Suite 14.2 ISE进行合成,并在Virtex 6 FPGA板(XC6VLX240T-3FF1156)上进行原型设计,并使用Xilinx ISIM模拟器进行验证。当使用中等大小的非矩形se对高分辨率图像进行测试时,该架构提供了实时性能,结果优于现有的收缩阵列实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Genetic Algorithm with Mixed Crossover approach for Travelling Salesman Problem An Empirical Study on Fault Prediction using Token-Based Approach Implementing an Authentication Mechanism for Machine Deletion on the Cloud Multi-agent Web Service Composition using Partially Observable Markov Decision Process Forecasting Stock Market Movements Using Various Kernel Functions in Support Vector Machine
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1