Please use this identifier to cite or link to this item:
Title: Smile challenger
Authors: Ang, Shi Chao
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2017
Abstract: A smile is a form of facial expression that are normally closely associated with happiness. Given that a smile can be measured, can we measure happiness and turn it into a fun Smile Challenger game? This paper presents an efficient approach to analyze a smile and assign a reasonable score (0 – 100%) to it. The study adopted a Mouth-Corner Features (MCFs)-based algorithm in determining the intensity of a smile. Through digital image processing techniques, it made use of a deterministic Inverse Binary Thresholding method to extract the MCFs from the image. With the two corners of the mouth detected, the algorithm then computes the Smile Score. The Smile Score, which categorized different classification of a smile, is consisted of 85% Corner Width Score and 15% Wrinkle Density Score. Smile Challenger’s algorithm was tested with 300 face images and had achieved an accuracy 71.7%.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
Smile Challenger Final Year Project (FYP) Report - Ang Shi Chao.pdf
  Restricted Access
Smile Challenger Final Year Project (FYP) Report2.15 MBAdobe PDFView/Open

Page view(s)

Updated on Jun 19, 2021


Updated on Jun 19, 2021

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.