Edge Feature based Moving Object Detection Using Aerial Images: A Comparative Study

Zainal Rasyid Mahayuddin, A Saif

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

Edge features or characteristics are the significant local intensity variation of pictorial structure in an image or frame or video sequence. Edge detection process finds the existence and position of pixels causes by significant differences in intensity of the images or frames or video sequences. However, selection of appropriate edge features specially to detect moving objects using aerial types of video sequences is still an elusive research concern because of various constraints for aerial frames, i.e. various altitudes, lack of features available for detection, motion variation etc. This research proposes comparative evaluation of different edge features based moving object detection methods to make it easy to decide which edge features based detection method is appropriate for extraction of moving object from aerial frames. Proposed research selected three edge features for detection, i.e. Sobel, Prewitt and Canny for moving object extraction to process high and low pictorial brightness variation for aerial video sequences. Proposed research illustrates the comparative performance of edge features based moving object detection. Each of the method is evaluated with extensive experimental analysis with standard performance metrics. Experimental results demonstrate effective comparison among each method with various performance metrics to ensure optimum detection performance for moving objects.
Original languageEnglish
Title of host publication2020 6th International Conference on Computing Engineering and Design (ICCED)
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-7281-9189-8
DOIs
Publication statusPublished - 2021
MoE publication typeA4 Conference publication
EventInternational Conference on Computing Engineering and Design - Sukabumi, Indonesia
Duration: 15 Oct 202016 Oct 2020
Conference number: 6

Conference

ConferenceInternational Conference on Computing Engineering and Design
Abbreviated titleICCED
Country/TerritoryIndonesia
CitySukabumi
Period15/10/202016/10/2020

Keywords

  • Computer Vision (CV)
  • Image Processing
  • Pattern Recognition

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