Generalized playfield segmentation of sport videos using color features

  • Authors:

  • Mao-Hsiung Hung;Chaur-Heh Hsieh;Chung-Ming Kuo;Jeng-Shyang Pan

  • Affiliations:

  • Dept. of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan;Dept. of Computer and Communication Engineering, Ming Chuan University, Gui-Shan, Taoyuan 333, Taiwan;Dept. of Information Engineering, I-Shou University, Dahsu, Kaohsiung 840, Taiwan;Dept. of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2011

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Abstract

This paper proposes a generalized method for playfield segmentation of various sport videos. It first estimates the probability density function (pdf) of color components of an image frame. Two hill-climbing schemes, which employ two-dimensional pdf and one-dimensional pdf, respectively, are proposed for clustering. Next, a novel algorithm that utilizes the domain knowledge of sport playfields is developed to merge those clusters into four color classes: red, green, blue, and gray. Finally, a simple scheme fuses small regions into their adjacent large regions to obtain the segmentation result. The experimental results indicate that the proposed method effectively segments the playfield regions of various sport videos.