Data Augmentation and Feature Fusion for Melanoma Detection with Content Based Image Classification

  • Rik Das
  • Sourav De
  • Siddhartha BhattacharyyaEmail author
  • Jan Platos
  • Vaclav Snasel
  • Aboul Ella Hassanien
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 921)


Computer aided diagnosis has leveraged a new horizon for accurate diagnosis of numerous fatal diseases. Melanoma is considered as one of the most lethal form of skin cancer which is increasingly affecting the population in recent times. The disease can be completely healed if diagnosed and addressed at an early stage. However, in most of the cases patients receive delayed care which results in fatal consequences. The authors have attempted to design an automated melanoma detection system in this work by means of content based image classification. Extraction of content based descriptors can nullify the requirement for manual annotation of the dermoscopic images which consumes considerable time and effort. The work has also undertaken a fusion based approach for feature combination for evaluating classification performances of hybrid architecture. The results have outclassed the state-of-the-art outcomes and have established significant performance improvement.


Computer aided diagnosis Melanoma Content based image classification Feature fusion Colour histogram HOG 



This work was supported by the ESF in “Science without borders” project, reg. nr. CZ.02.2.69/0.0/0.0/16_027/0008463 within the Operational Programme Research, Development and Education.

Dr. Rik Das would like to acknowledge Calcutta University Data Science group for continuous brainstorming and support towards innovative research ideas relevant to this work.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Rik Das
    • 1
  • Sourav De
    • 2
  • Siddhartha Bhattacharyya
    • 3
    Email author
  • Jan Platos
    • 3
  • Vaclav Snasel
    • 3
  • Aboul Ella Hassanien
    • 4
  1. 1.Department of Information TechnologyXavier Institute of Social ServiceRanchiIndia
  2. 2.Department of Computer Science and EngineeringCooch Behar Government Engineering CollegeCooch BeharIndia
  3. 3.Faculty of Electrical Engineering and Computer ScienceVSB Technical University of OstravaOstravaCzechia
  4. 4.Cairo UniversityGizaEgypt

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