Artificial Intelligence Based Skin Classification Using GMM

  • M. Monisha
  • A. SureshEmail author
  • M. R. Rashmi
Patient Facing Systems
Part of the following topical collections:
  1. Wearable Computing Techniques for Smart Health


This study describes the usage of neural community based on the texture evaluation of pores and skin a variety of similarities in their signs, inclusive of Measles (rubella), German measles (rubella), and Chickenpox etc. In fashionable, these illnesses have similarities in sample of infection and symptoms along with redness and rash. Various skin problems have similar symptoms. For example, in German measles (rubella), Chicken pox and Measles (rubella) a similarity can be observed in skin rashes and redness. The prognosis of skin problems take a long time as the patient’s previous medical records, physical examination report and the respective laboratory diagnostic reports have to be studied. The recognition and diagnosis get tough due to the complexity involved. Subsequently, a computer aided analysis and recognition gadget would be handy in such cases. Computer algorithm steps include image processing, picture characteristic extraction and categorize facts with the help of a classifier with Artificial Neural Network (ANN). The ANN can analyze the patterns of symptoms of a particular disease and present faster prognosis and reputation than a human doctor. For this reason, the patients can undergo the treatment for the pores and skin problems based totally on the symptoms detected.


Gaussian mixture model classifier (GMM) Pre-processing Dominant rotated local binary pattern (DRLBP) Gray level co-occurrence matrix (GLCM) Super pixel segmentation Probabilistic neural network (PNN) classification 


Compliance with ethical standards

Conflict of interest

The authors have no conflict of interest.

Ethical approval

Animals were not involved. This article does not contain any studies with human participants performed by any of the authors. This article does not contain any studies with human participants or animals performed by any of the authors.


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.S.A. Engineering College, Anna UniversityChennaiIndia
  2. 2.S.A. Engineering CollegeChennaiIndia
  3. 3.Amrita School of EngineeringBengaluruIndia

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