Design and Realization of Improved Sobel Edge Detection Algorithm Based on FPGA

CAO Yang; SU Li-na; SHEN Qi; GU Xiao-feng

Chinese

您当前的位置：

首页 >

文章列表页 >

Design and Realization of Improved Sobel Edge Detection Algorithm Based on FPGA

更新时间：2026-09-04

- Design and Realization of Improved Sobel Edge Detection Algorithm Based on FPGA
- Vol. 29, Issue 10, Pages: 124-127(2012)
- 作者机构：
  
  轻工过程先进控制教育部重点实验室机构 , 江南大学电子工程系,江苏,无锡,214122
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2012
- 稿件说明：
移动端阅览
曹杨, 苏丽娜, 沈琪, 顾晓峰. 一种改进的Sobel边缘检测算法的设计及其FPGA实现[J]. 微电子学与计算机, 2012, 29(10): 124-127,132.

CAO Yang, SU Li-na, SHEN Qi, et al. Design and Realization of Improved Sobel Edge Detection Algorithm Based on FPGA[J]. 2012, 29(10): 124-127.
曹杨, 苏丽娜, 沈琪, 顾晓峰. 一种改进的Sobel边缘检测算法的设计及其FPGA实现[J]. 微电子学与计算机, 2012, 29(10): 124-127,132. DOI：

CAO Yang, SU Li-na, SHEN Qi, et al. Design and Realization of Improved Sobel Edge Detection Algorithm Based on FPGA[J]. 2012, 29(10): 124-127. DOI：

摘要

为了快速得到边缘更清晰、敏感度更高的实时边缘图像数据

提出了一种改进的Sobel边缘检测算法.对原始图像的边缘进行平滑滤波后

利用2个3×3模板对选定的二维图像中同样大小区域内的数据进行卷积

合并水平及垂直方向的导数得到该区域的梯度值

再通过添加的梯度方向模块对该区域进行4个方向的判断以帮助确定边缘

最后通过非极大值抑制及二值化处理确定图像边缘.将改进后的Sobel边缘检测算法在FPGA上进行了实现并证明了其有效性.

Abstract

An improved Sobel edge detection algorithm has been proposed to obtain the real-time edge of image data quickly with sharper edge and higher sensitivity.After applying the smoothing filter to the edge of the original image

two 3×3 templates are used to perform convolution on the data of the same size region in the selected two-dimensional image.The gradient values of this region can be obtained by combining the horizontal and vertical direction derivatives.Then

the gradient direction module is used to help judging the four directions of this region and defining the edge.The image edge is finally determined by non-maxima suppression and binarization.The improved Sobel edge detection algorithm is realized based on the FPGA and proved to be effective.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A review of large model development: technological evolution from BERT to Deepseek

Microservices anomaly detection based on the correlation of monitoring metrics

Aerial vehicle detection algorithm based on multi-scale fusion and small-object enhancement

Research on the design of blockchain-based AI-generated content traceability framework

Monte carlo analysis of V-layout trench SiC neutron detector

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰