Laser & Optoelectronics Progress, Volume. 55, Issue 1, 11009(2018)

Block Color Feature Extraction Algorithm Based on Mixed Color Space

Wang Min, Wang Jing*, Zhang Licai, and Zhang Xin
Author Affiliations
  • School of Information and Control Engineering, Xi''an University of Architecture and Technology, Xi''an, Shaanxi 710055, China
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    Figures & Tables(11)
    Block image
    Flow chart of feature fusion
    Color moment in mixed color space
    Light color moment in mixed color space
    Part identification results of Chinese paintings
    Comparison of the recognition precision of different spatial color features combined with texture feature
    • Table 1. Recognition precision of different spatial color features combined with texture feature%

      View table

      Table 1. Recognition precision of different spatial color features combined with texture feature%

      Color spaceLandscapeFlower and birdBambooPersonHorse
      HSV84.3385.3183.9384.4583.96
      HIS84.6184.5283.8483.5784.08
      YUV82.9783.6283.2282.2983.26
      Mixed color space88.2589.2688.8388.7987.87
      Block mixed color space90.0290.6789.8590.6189.92
    • Table 2. Recognition recall of different spatial color features combined with texture feature%

      View table

      Table 2. Recognition recall of different spatial color features combined with texture feature%

      Color spaceLandscapeFlower and birdBambooPersonHorse
      HSV83.6385.9384.1683.9582.78
      HIS85.2683.9883.2983.8584.21
      YUV83.2284.2483.7682.9183.36
      Mixed color space89.0189.6388.3388.4387.72
      Block mixed color space90.8991.0290.6590.2790.62
    • Table 3. Recognition time of different spatial color features combined with texture feature

      View table

      Table 3. Recognition time of different spatial color features combined with texture feature

      Color spaceMean ofprecision /%Recognitiontime /s
      HSV84.400.6
      HIS84.120.6
      YUV83.000.6
      Mixed color space88.602.1
      Block mixed color space90.212.9
    • Table 4. Recognition precision of different spatial color features combined with texture feature%

      View table

      Table 4. Recognition precision of different spatial color features combined with texture feature%

      Color spacePersonCarsSightsArchitectureMean
      HSV81.6682.3581.8782.5182.09
      HIS81.8982.9681.5782.7582.29
      YUV81.1282.5481.0382.9181.90
      Mixed color space86.5587.5886.9187.7787.20
      Block mixed color space89.9290.3889.9890.2190.12
    • Table 5. Recognition recall of different spatial color features combined with texture feature%

      View table

      Table 5. Recognition recall of different spatial color features combined with texture feature%

      Color spacePersonCarsSightsArchitectureMean
      HSV82.0382.3482.6882.9782.50
      HIS81.9282.2382.0982.8782.28
      YUV81.6582.5382.0682.9182.29
      Mixed color space88.6289.0388.7889.6489.01
      Block mixed color space90.9791.8690.2390.7690.96
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    Wang Min, Wang Jing, Zhang Licai, Zhang Xin. Block Color Feature Extraction Algorithm Based on Mixed Color Space[J]. Laser & Optoelectronics Progress, 2018, 55(1): 11009

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    Paper Information

    Category: Image Processing

    Received: Jul. 12, 2017

    Accepted: --

    Published Online: Sep. 10, 2018

    The Author Email: Wang Jing (864425860@qq.com)

    DOI:10.3788/LOP55.011009

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