Abstract
Plastic surgery alters original facial features of an individual thereby making Face Recognition after plastic surgery difficult. Cosmetic procedures introduce geometrical deviations which are difficult to analyze by state of the art facial identification procedures. Here a region based score level fusion approach for local facial features is proposed to equalize former and latter surgery images. Steps involved in the recognition process are; firstly identifying the ROIs (areas/regions of interest/concern) of before and after surgery images. ROIs are eyes, nose and mouth regions; feature extraction from identified regions via Speeded Up Robust Features and K Nearest Neighbour techniques; region wise and full face geometrical distance calculation between matched feature vectors of pre and post surgery image samples by a distance metric (sum of squared differences); final recognition rate calculation by weighted score level fusion. The projected procedure gives recognition of 89.7% for local surgical treatment and 87% for global surgery.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
