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A dynamic portrait segmentation by merging colors and depth information

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  • Intelligent and Information Systems
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Abstract

In this paper, we proposed a new method to improve the dynamic portrait segmentation in Kinect which always causes the problem of incomplete image segmentation of portrait due to the loss of the depth. This problem can be solved by using the color information to reinforce the areas where the depth is uncertain. We can segment the portrait’s foreground more completely using the proposed method. First, the depth information can be divided into foreground, background, uncertain areas to produce a judging area for the foreground’s uncertain areas. Secondly, the volunteer image will be segmented by Sobel edge detection, watershed and other steps in color information then be treated as the characteristic value of color area to calculate the mean value and standard deviation respectively. Finally, we chose the best image from these processing by comparing the color feature of the foreground edge and the judging area. The results show that we can completely segment out the portrait image as well as reduce its error rate significantly.

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Authors and Affiliations

  1. Department of Civil Engineering, and The Key Lab of Digital Signal and Image Processing of Guangdong Province, Shantou University, Guangdong, P. R. China

    Li-Hong Juang

  2. Department of Information Management, National Taichung University of Technology, Taichung, Taiwan, ROC

    Ming-Ni Wu & Feng-Mao Tsou

Authors
  1. Li-Hong Juang
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  2. Ming-Ni Wu
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  3. Feng-Mao Tsou
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Corresponding author

Correspondence to Li-Hong Juang.

Additional information

Recommended by Associate Editor Kang-Hyun Jo under the direction of Editor Euntai Kim.

This journal was supported by the Shantou University, Scientific Research Foundation for Talents plan. The authors deeply acknowledge the financial support from Shantou University, Guangdong, P. R. China under the STU Scientific Research Foundation for Talents plan.

Li-Hong Juang received his B.S. degree in Civil Engineering from the National Chiao Tung University, Taiwan in 1990 and an M.S. degree in Applied Mechanics from the National Taiwan University, Taiwan in 1993, and a Ph.D. degree in Control and Embedded System group from Department of Engineering at Leicester University, UK, in 2006. His research interests are in the analysis, modeling, smart system design, image process, robot control and system biologic control.

Ming-Ni Wu received her Ph.D. degree in Computer Science & Information Engineering, National Chung Cheng University, Taiwan. Her research interests are in image process and information management.

Feng-Mao Tsou received his M.S. degree from the Department of Information Management, National Taichung University of Technology, Taiwan. His research interests is in image process.

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Juang, LH., Wu, MN. & Tsou, FM. A dynamic portrait segmentation by merging colors and depth information. Int. J. Control Autom. Syst. 13, 1286–1293 (2015). https://doi.org/10.1007/s12555-014-0313-z

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  • DOI: https://doi.org/10.1007/s12555-014-0313-z

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