Abstract

Recently medical cosmetic has attracted significant business opportunity. Micro cosmetic surgery usually involves invasive cosmetic procedures such as non-ablative laser procedure for skin rejuvenation. However, to select an appropriate treatment for skin relies on accurate preoperative evaluations. In this paper, an automatic facial skin defects detection and recognition method is proposed. The system first locates the facial region from the input image. Then, the shapes of faces were recognized using a contour descriptor. The facial features are extracted to define regions of interest and an image segment method is used to extract potential defect. A support-vector-machine-based classifier is then used to classify the potential defects into spots, acnes and normal skin. Experimental results demonstrate effectiveness of the proposed method.

Highlights

  • Because the forehead is an important part in medical cosmetology, every subject is asked to move their hair aside in order to show their forehead

  • The proposed system first locates the facial region from the input image

  • An approximate Poisson distribution is used to define a suitable threshold for extracting potential defects

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Summary

Introduction

Medical cosmetology has a great development. It usually involves invasive cosmetic procedures or operation such as non-ablative laser procedure for skin rejuvenation and filling injection to relieve wrinkles [1,2]. With gradually higher resolution in digital cameras, many digital imaging methods have been proposed to analyze skin conditions [4,5,6,7]. These investigations applied various color quantization methods to distinguish whether the ROI is a spot or not. A novel skin conditions evaluation system, which integrates a multi-view image acquisition device and automatic facial skin defect detection, is proposed in this paper.

The Proposed System
ROI Extraction
Classification
Experiment Environment
Experimental Database
Face View Classification Result
Defect Detection Result
Conclusions and Future Directions
Full Text
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