Investigation of Abnormal Skin Lesion Analysis System for Melanoma Early Detection Using Image Processing

  • Authors

    • M. Sheriff
    • K. Dinakaran
    • M. Kumaran
    • B. Saikiran
    • I. Vikram
    https://doi.org/10.14419/ijet.v7i4.6.28931
  • K-Means, Fuzzy-C, Chan Vese, ROI (Region Of Interest), accuracy, sensitivity, precision, F measure Ada boost, GLCM( gray-level co-occurrence matrix) Melanoma, Lesion.

  • Abstract

    In this paper, acquisition of lesion image is carried out and compared using three different segmentation algorithm. Otsu’s method based thresholding technique is used to minimize variance of the background and foreground pixels. Here tone detection and exclusion, three ROI segmentation models (K-means, Fuzzy-C means, Chan Vese model) followed by hybrid feature extraction, and classification methods are carried out. Accuracy, sensitivity, precision , F measure of the acquired lesion image are obtained by using the above segmentation methods and the best method is examined.

     

     

  • References

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  • How to Cite

    Sheriff, M., Dinakaran, K., Kumaran, M., Saikiran, B., & Vikram, I. (2018). Investigation of Abnormal Skin Lesion Analysis System for Melanoma Early Detection Using Image Processing. International Journal of Engineering & Technology, 7(4.6), 567-572. https://doi.org/10.14419/ijet.v7i4.6.28931

    Received date: 2019-04-22

    Accepted date: 2019-04-22