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Facial mark detection and removal using graph relations and statistics

Hosseini, M. M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/IranianCEE.2017.7985432
  3. Abstract:
  4. Face Analysis is an important task in image processing. Most of these tasks centralized on face recognition and detection. One of different ways for deceiving automatic face analysis systems is mark notation on the skin. On the other hand some applications attempts to eliminate defects of the face. Hence, in this paper we try to detect and remove skin marks on the face, whether they're natural or not. Our algorithm passes face image through appropriate filters to get mark candidates and then create a graph space using 8-point neighborhood relations of mark candidates image pixels. Then we compute probabilities of each mark candidate using four measures based on intensity of occurrence, shape density, uniqueness in local area and color difference. Then using a threshold, we distinguish marks and false candidates. Finally we use the most similar adjacent area around mark to remove the mark from skin. Our algorithm represents significant accuracy in mole detection and removal. © 2017 IEEE
  5. Keywords:
  6. Mark detection ; Mark removal ; Colorimetry ; Image processing ; Centrality ; Color difference ; Connected component ; Face ; Face analysis ; Mole ; Neighborhood relation ; Shape density ; Face recognition
  7. Source: 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, 2 May 2017 through 4 May 2017 ; 2017 , Pages 2223-2228 ; 9781509059638 (ISBN)
  8. URL: https://ieeexplore.ieee.org/document/7985432