Motion detection by using entropy image and adaptive state-labeling technique

Meng Chou Chang, Yong Jie Cheng

Research output: Contribution to journalConference articlepeer-review

14 Citations (Scopus)


This paper proposes an improved motion detection method based on the entropy image and the adaptive state-labeling algorithm. In our method, a spatio-temporal sliding window is built for each pixel, and the pixels in the sliding window are assigned state labels according to our adaptive state-labeling technique. The state label distribution in the sliding window is used to construct the entropy image, in which a pixel with lower entropy is considered as part of a moving object In this paper, we have compared our motion detection method with the MRF (Markov random field) based method, the STEI (spatio-temporal entropy image) method, and the DSTEI (difference-based spatio-temporal entropy image) method. Experimental results show that our motion detection method is robust and has lower computational complexity.

Original languageEnglish
Article number4253476
Pages (from-to)3667-3670
Number of pages4
JournalProceedings - IEEE International Symposium on Circuits and Systems
Publication statusPublished - 2007 Sep 27
Event2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007 - New Orleans, LA, United States
Duration: 2007 May 272007 May 30

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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