NDLI: Detection and recognition of moving objects using the temporal difference method and the hidden Markov model

Content Provider	IEEE Xplore Digital Library
Author	Wanhyun Cho Sunworl Kim Gukdong Ahn
Copyright Year	2011
Description	Author affiliation: Dept. Statistics, Chonnam National University, Gwangju, South Korea (Wanhyun Cho; Sunworl Kim) \|\| Dept. Statistics, Chonnam National University, Gwanggju, South Korea (Gukdong Ahn)
Abstract	This paper proposes a new detection and recognition method for moving objects that uses the temporal difference method (TDM) and the hidden Markov model (HMM). First, we apply the concept of entropy to convert the pixel value in the image domain into the amount of energy change in the entropy domain. Second, we use the temporal difference method to quickly detect the region of moving objects in complex images to address the variation in changing environments. Third, we use the discrete wavelet transformation technique to extract proper feature vectors from the detected mask image. Fourth, we use the hidden Markov model to accurately recognize moving objects. The results indicate that our proposed method can effectively and accurately detect and recognize moving objects in image sequences.
Starting Page	119
Ending Page	123
File Size	225136
Page Count	5
File Format	PDF
ISBN	9781424487271
e-ISBN	9781424487288
DOI	10.1109/CSAE.2011.5952815
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Temporal Difference Method Discrete Wavelet Transformation Entropy Hidden Markov Model Detection and Recognition of Moving Objects
Content Type	Text
Resource Type	Article

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