JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (2): 63-70.doi: 10.6040/j.issn.1672-3961.0.2016.174

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Object detection algorithm based on Bayesian probability estimation in wavelet domain

LIU Yingxia1, WANG Xichang2, TANG Xiaoli3, CHANG Faliang4   

  1. 1. Shandong Communication and Media College, Jinan 250200, Shandong, China;
    2. Shandong Province Academy of Education Recruitment and Examination, Jinan 250011, Shandong, China;
    3. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, West Harrison 10606, New York, America;
    4. School of Control Science and Engineering, Shandong University, Jinan 250011, Shandong, China
  • Received:2016-05-23 Online:2017-04-20 Published:2016-05-23

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Abstract: In order to improve the detection algorithm, Bayesian probability estimation model in wavelet domain was built to get a robust threshold, and the detected object could be obtained with the adaptive threshold. Moving Window-Based Double Haar Wavelet Transform for detected image sequence was finished. Bayesian probobility estimation model based on kernel density function was built for low frequency part, and adaptive threshold could be obtained after training and studying. With the threshold to judge the low frequnency part, the binary image could be got. Six video sequences with one targe and multiple targets outdoor and indoor were employed to evaluate the effectiveness of presented algorithm. Experimental results showed that it could give a better detecting results.

Key words: Bayesian probability estimation, object detection, wavelet domain, dynamic background

CLC Number: 

  • TP181
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