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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM52575
Volume:
9 |
9 |
Sep 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Vitiligo is a chronic dermatological condition characterized by depigmentation of the skin. This study proposes a Convolutional Neural Network (CNN)-based system for automated detection of vitiligo from skin images. The model uses a pipeline consisting of image preprocessing (normalization, resizing, augmentation), followed by a deep learning classifier trained to distinguish between healthy and vitiligo affected skin. The system is integrated into a three-tier web application (VitiScan) using React for frontend, Flask for backend, and a PyTorch-based model. Evaluation metrics including accuracy, precision, recall, and F1-score confirm the system’s reliability. The proposed model enhances diagnostic capabilities and offers a potential assistive tool for dermatologists.
KEYWORDS
Publication Date
9/14/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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