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Hole filling using joint bilateral filtering for moving object segmentation

[+] Author Affiliations
Ran Liu

Chongqing University, College of Communication Engineering, Chongqing 400044, China

Chongqing Key Laboratory of Software Theory and Technology, Chongqing 400044, China

Chongqing University, Key Laboratory of Dependable Service Computing in Cyber Physical Society of the Ministry of Education, Chongqing 400044, China

Bole Li

Chongqing University, College of Communication Engineering, Chongqing 400044, China

Zhengwei Huang

Chongqing University, College of Communication Engineering, Chongqing 400044, China

Donghua Cao

Chongqing Key Laboratory of Software Theory and Technology, Chongqing 400044, China

Chongqing University, Key Laboratory of Dependable Service Computing in Cyber Physical Society of the Ministry of Education, Chongqing 400044, China

Yingchun Tan

Chongqing University, College of Communication Engineering, Chongqing 400044, China

Zekun Deng

Chongqing University, College of Communication Engineering, Chongqing 400044, China

Miao Xu

Chongqing Key Laboratory of Software Theory and Technology, Chongqing 400044, China

Chongqing University, Key Laboratory of Dependable Service Computing in Cyber Physical Society of the Ministry of Education, Chongqing 400044, China

Ruishuang Jia

Chongqing Key Laboratory of Software Theory and Technology, Chongqing 400044, China

Chongqing University, Key Laboratory of Dependable Service Computing in Cyber Physical Society of the Ministry of Education, Chongqing 400044, China

Weimin Tan

Chongqing University, College of Communication Engineering, Chongqing 400044, China

J. Electron. Imaging. 23(6), 063021 (Dec 18, 2014). doi:10.1117/1.JEI.23.6.063021
History: Received April 11, 2014; Accepted November 10, 2014
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Abstract.  Due to various reasons (e.g., poor quality of image, sudden changes in light conditions, occlusions, or objects with similar colors), holes may appear in the moving object region when performing moving object segmentation. How to remove these holes is a crucial problem in high-quality segmentation. A moving object segmentation approach combining symmetrical differencing and joint bilateral filtering is proposed. One important aspect of our approach is that joint bilateral filtering is used to eliminate/reduce the holes in the moving object region, which makes the extracted moving object more accurate and complete, in many cases in contrast to the reference temporal difference approaches. The approach first performs block-based symmetrical differencing to obtain coarse moving object regions. Then, a joint bilateral filter that uses the current gray image as a guide image is adopted to smooth the difference image. Next, edge detection is performed on the smoothed difference image and the current gray image, respectively, to get the edges of moving objects. Finally, the undesired background is distinguished from the moving object and is cut off by a postprocessing module. In addition, the fast joint bilateral filters that can be used as substitutes for the classical joint bilateral filter are discussed. Experimental results show that this approach can effectively fill the holes in the moving object region and provide an improvement in accuracy of moving object segmentation in many cases.

© 2014 SPIE and IS&T

Citation

Ran Liu ; Bole Li ; Zhengwei Huang ; Donghua Cao ; Yingchun Tan, et al.
"Hole filling using joint bilateral filtering for moving object segmentation", J. Electron. Imaging. 23(6), 063021 (Dec 18, 2014). ; http://dx.doi.org/10.1117/1.JEI.23.6.063021


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