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Asian Journal of Information Technology

ISSN: Online 1993-5994
ISSN: Print 1682-3915
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Segmentation of Moving Objects Using a Mutual- Information Based Combination Scheme

Yaming Wang , Yunhua Zhang , Li Cao , Weida Zhou and Wenqing Huang
Page: 218-222 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

To segment the moving objects from image sequence is an important problem in computer vision. In this paper, a novel approach is proposed for moving objects segmentation from grayscale image sequence. In order to increase the robustness of segmentation, the information-theoretic principle of mutual information is proposed to combine two different segmentation results. First, the adaptive Gaussian distribution model for each image pixel is presented. Based on this model, each image frame is mapped from spatial domain to statistic domain. The segmentation is consequently performed in statistic domain. Meanwhile the image frame is segmented using Otsu`s method (Otsu, N., 1979) This two segmentation results are then combined by using mutual information and the final result is obtained. Experimental results from a real image sequence show the feasibility of the proposed approach.


How to cite this article:

Yaming Wang , Yunhua Zhang , Li Cao , Weida Zhou and Wenqing Huang . Segmentation of Moving Objects Using a Mutual- Information Based Combination Scheme.
DOI: https://doi.org/10.36478/ajit.2005.218.222
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2005.218.222