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[An automatic color correction algorithm for digital human body sections].

Bin Zhuge, He-qin Zhou, Lei Tang

    Hang Tian Yi Xue Yu Yi Xue Gong Cheng = Space Medicine & Medical Engineering
    |September 16, 2005
    PubMed
    Summary
    This summary is machine-generated.

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    This study introduces an automated algorithm to enhance color consistency in human body image datasets. The new method quickly improves color parameter uniformity for digital imaging applications.

    Area of Science:

    • Digital imaging
    • Medical illustration
    • Image processing

    Background:

    • Serial section images of the human body often exhibit color variations.
    • Inconsistent color parameters can hinder accurate analysis and visualization.
    • Standardization of color is crucial for large-scale digital human databases.

    Purpose of the Study:

    • To develop an automated approach for improving color parameter uniformity in human body serial section images.
    • To establish a rapid and efficient method for color correction in digital imaging datasets.

    Main Methods:

    • An automated color correction algorithm was developed using the RGB color space and a standard CMYK color chart.
    • The algorithm auto-segments the gray portion of the color chart to obtain gray values.

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  • A transformation function and lookup table are generated to correct image colors based on standard gray values.

    • Main Results:

    • The algorithm successfully corrected the color of the Chinese Digital Human Girl No. 1 (CDH-G1) database.
    • Color correction for a single image took approximately 13.475 seconds on a personal computer.
    • The developed method demonstrated rapid and automatic color correction capabilities.

    Conclusions:

    • The proposed algorithm effectively corrects image colors automatically and swiftly.
    • The uniformity of color parameters in the corrected dataset is significantly improved.
    • This approach offers a valuable tool for standardizing color in digital human imaging.