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Outlier Detection in Object Counting based on Hue and Distance Transform using Median Absolute Deviation (MAD)

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

Abstract

Object counting based on image data has been developed in many research. It is fast, automatic and noncontact solution that is applied in health, microbiology, object tracking, robotics and industry. During the counting, object that differs from majority object might be presented in a frame. This outlier object should be detected and not be counted. This study present an algorithm to detect outliers in object counting based on color and shape information. The color was based on Hue whilst the shape was based on distance transform. Both features were chosen as it is invariant to position and rotation in plane. Outlier detection utilized Median Absolute Deviation (MAD) on Histograms of both features. The testing shows promising result (accuracy of 94.3%) in 35 images with simple background.

Original languageEnglish
Title of host publicationProceedings of 2019 4th International Conference on Sustainable Information Engineering and Technology, SIET 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages217-222
Number of pages6
ISBN (Electronic)9781728138787
DOIs
Publication statusPublished - Sept 2019
Event4th International Conference on Sustainable Information Engineering and Technology, SIET 2019 - Lombok, Indonesia
Duration: 28 Sept 201930 Sept 2019

Publication series

NameProceedings of 2019 4th International Conference on Sustainable Information Engineering and Technology, SIET 2019

Conference

Conference4th International Conference on Sustainable Information Engineering and Technology, SIET 2019
Country/TerritoryIndonesia
CityLombok
Period28/09/1930/09/19

Keywords

  • distance transform
  • hue
  • median absolute deviation
  • object counting
  • outlier detection

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