Fast K-Means Technique for Segmentation of ‎Dermoscopic Images

  • Authors

    • Saravana Kumar V. Galgotias University, Greater Noida, Uttar Pradesh, India
    • Kavitha M. S A Engineering College, AVADI, Chennai, Tamilnadu, India
    • Revatthy K. New Horizon College of Engineering, Bengaluru, Karnataka, India
    • Anantha Siva Prakasam New Horizon College of Engineering, Bengaluru, Karnataka, India
    • Bavya S CGI, Chennai, Tamilnadu, India
    https://doi.org/10.14419/ppzpx689

    Received date: January 9, 2026

    Published date: January 12, 2026

  • Fast K-Means; K-Means, Segmentation; Skin Lesion; Melanoma

  • Abstract

    Skin cancer remains one of the hazardous cancers diagnoses each year and accounts for more ‎than 50%. When detected at its early stage, standard and cost-effective therapies can treat it ‎successfully - classifying skin sores carefully is key to automating early end systems and ‎mitigating risk factors. Melanoma can provide both shape features and areas of desire for ‎surface examination. Unfortunately, its prevalence can be both unpredictable and lethal, ‎leading to multiple times more passes than all other skin cancers combined. The proposed ‎method demonstrates about the Fast K-Means clustering technique. It can be applied on the ‎dermoscopic skin lesion images which can convert into L*u*v. This approach is then ‎compared with the outcomes of K-Means and Fuzzy C-Means. Evaluation has carried outs ‎includes number of pixels and time complexity analysis. Crystal clear, the proposed method is ‎obviously segmented the lesion and display any visible lesions or spots on them‎.

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  • How to Cite

    V. , S. K. ., M. , K. ., K. , R. ., Prakasam , A. S. ., & S , B. (2026). Fast K-Means Technique for Segmentation of ‎Dermoscopic Images. International Journal of Basic and Applied Sciences, 15(1), 59-67. https://doi.org/10.14419/ppzpx689