International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.

Edge Detection on Field Programmable Gate Array (FPGA)

Author(s) Pallavi Sahay, Avinash Kumar Singh, Diksha Sahay
Country India
Abstract Edges are significant local changes in the image and are very important features for analysing images. Edges typically occur on the boundary between two different regions in an image. An edge in an image is a significant local change in the image intensity, usually associated with a discontinuity in either the image intensity or the first derivative of the image intensity. Edge detection is one of the tools that can be used in many image processing applications for withdrawing information from image. Sobel edge detection is one of the operators that operate on gradient based edge selection methods to find edge pixels in the image. This report proposed an implementation of Sobel edge Detection algorithm to find the pixels in grayscale images. We present a video streaming architecture and IP implementation using high level synthesis. A video with 720p resolution streamed from the HDMI source and real time edge detected video captured on another monitor. For implementation, ZYBO board or kit is used with Vivado software with 2018.3 V, which has provided adequate peripherals for implementation.
Keywords Sobel, Edge, FPGA, High Level Language, Gradient, Register Transfer Level, IP
Field Engineering
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-03-18
Cite This Edge Detection on Field Programmable Gate Array (FPGA) - Pallavi Sahay, Avinash Kumar Singh, Diksha Sahay - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.15044
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.15044
Short DOI https://doi.org/gtnkdd

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