Implementation of Image Segmentation with Prewitt Edge Detection using VLSI Technique

  • N. Prakash
  • , Syed Asif Basha
  • , Subrata Chowdhury
  • , B. Reshmi
  • , Dhiraj Kapila
  • , S. Devi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Edge Detection is one of the discontinuity based image segmentation technique perform optimized function for detection, counting of people and other objects like vehicle, animals, etc in an image sequence. Edge detection is the technique bidding to designate the intensity changes concerned to the physical processes that have established them. Prewitt is one of the famous edge detection algorithms which use the derivative approximation to find the edges. This paper implements the Prewitt edge detection operator using VLSI design technique. Coding is written in VHDLand simulated using QUARTUS. The Simulation results are also compared with that of MATLAB outputs. The experimental results show that the proposed algorithm can be effectively used to detect objects in difficult videos of crowds with many occlusions, local noise and local scale variations.

Original languageEnglish
Title of host publicationProceedings of the 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665474139
DOIs
Publication statusPublished - 2022
Event2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022 - Chennai, India
Duration: 15-07-202216-07-2022

Publication series

NameProceedings of the 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022

Conference

Conference2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022
Country/TerritoryIndia
CityChennai
Period15-07-2216-07-22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems and Management
  • Electrical and Electronic Engineering
  • Instrumentation

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