Suspicious object detection using fuzzy-color histogram

Chi Hung Chuang, Jun Wei Hsieh, Luo Wei Tsai, Pei Shiuan Ju, Kao Chin Fan

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

7 Scopus citations


This paper proposes a novel method to detect suspicious objects from videos for abnormal event analysis. When considering a robbery event happens, there should be some suspicious object transferring conditions following between the forager and the victim. Since there is no prior knowledge about the object's property, it is difficult to automatically analyze the conditions without any manual efforts. To tackle this problem, a ratio histogram based on fuzzy c-means algorithm is proposed for finding suspicious objects. Furthermore, we use Gaussian mixture models to model the suspicious object's visual properties so that it can be accurately segmented from videos. After analyzing its subsequent motion features, different abnormal events like robbery can be effectively detected from videos. Experiment results have proved that the proposed method is robust, accurate, and powerful in abnormal event detection.

Original languageEnglish
Title of host publication2008 IEEE International Symposium on Circuits and Systems, ISCAS 2008
Number of pages4
StatePublished - 2008
Event2008 IEEE International Symposium on Circuits and Systems, ISCAS 2008 - Seattle, WA, United States
Duration: 18 May 200821 May 2008

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310


Conference2008 IEEE International Symposium on Circuits and Systems, ISCAS 2008
Country/TerritoryUnited States
CitySeattle, WA


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