Human Ear Print Detection Algorithm

Authors

  • Raniah Ali Mustafa Mustansiriyah University, Iraq
  • Haitham Salman Chyad Mustansiriyah University, Iraq
  • Dena Nadir George

DOI:

https://doi.org/10.31695/IJERAT.2020.3644

Keywords:

Ear Detection, HSV Color Space, Gaussian Filter, Contrast Enhancement, Canny Edge Detection

Abstract

    In this paper, proposed detection algorithm for human ear print images, the algorithm consist of three-stage. the first stage The detection algorithm using HSV color space, canny algorithm and contrast enhancement for grayscale. This step aims to determine skin area in-ear image by first HSV color space converting RGB to HSV color space and applying certain rules to determine the skin area. the second stage applies skin ear segmentation for the split of the skin and non-skin areas where ear skin color detection. After the ear detection stage, the first stage in edge detection is image smoothing through using a Gaussian filter then converted to a grayscale image after then contrast enhancement is an important step in the algorithm detection ear. Finally applying Canny edge detection, in general, is to significantly reduce the amount of data in an image, while protecting the main structure to be utilized for further image processing. were obtained from the dataset, available in the Internet and detection algorithm implemented in programing language Visual Basic 6.0.

References

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How to Cite

Raniah Ali Mustafa, Haitham Salman Chyad, & Dena Nadir George. (2020). Human Ear Print Detection Algorithm . International Journal of Engineering Research and Advanced Technology (ijerat) (E-ISSN 2454-6135) DOI: 10.31695/IJERAT, 6(8), 90–104. https://doi.org/10.31695/IJERAT.2020.3644

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Articles