Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 
ORIGINAL ARTICLE
Year : 2020  |  Volume : 16  |  Issue : 1  |  Page : 40-52

Detecting anomalous growth of skin lesion using threshold-based segmentation algorithm and Fuzzy K-Nearest Neighbor classifier


Department of Electronics and Communication Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India

Correspondence Address:
S Sivaraj
Department of Electronics and Communication Engineering, National Institute of Technology, Tiruchirappalli - 620 015, Tamil Nadu
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jcrt.JCRT_306_17

Rights and Permissions

Context: Skin cancer is a complex and life-threatening disease caused primarily by genetic instability and accumulation of multiple molecular alternations. Aim: Currently, there is a great interest in the prospects of image processing to provide quantitative information about a skin lesion, that can be relevance for the clinical images and also used as a stand-alone cautioning tool. Setting and Design: To accomplish a powerful approach to recognize skin cancer without performing any unnecessary skin biopsies, this article presents a new hybrid technique for the classification of skin images using Firefly with K-Nearest Neighbor algorithm (FKNN). Materials and Methods: FKNN classifier is used to predict and classify skin cancer along with threshold-based segmentation and ABCD feature extraction. Image preprocessing and feature extraction techniques are mandatory for any image-based applications. Statistical Analysis Used: Initially, it is essential to eliminate the illumination variation and the other unwanted shadow areas present in the skin image, which is done by homomorphic filtering called preprocessing. Results: The comparison of our proposed method with other existing methods and a comprehensive discussion is explored based on the obtained results. Conclusion: The proposed FKNN provides a quantitative information about a skin lesion through hybrid KNN and firefly optimization that helps for recognizing the skin cancer efficiently than other technique with low computational complexity and time.


[FULL TEXT] [PDF]*
Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed1432    
    Printed224    
    Emailed0    
    PDF Downloaded230    
    Comments [Add]    

Recommend this journal