eCite Digital Repository

A physiognomy based method for facial feature extraction and recognition


Liu, Y and Huang, ML and Huang, W and Liang, J, A physiognomy based method for facial feature extraction and recognition, Journal of Visual Languages and Computing, 43 pp. 103-109. ISSN 1045-926X (2017) [Contribution to Refereed Journal]

Copyright Statement

© 2017 Elsevier Ltd. All rights reserved.

DOI: doi:10.1016/j.jvlc.2017.09.006


This paper proposes a novel calculation method of personality based on Chinese physiognomy. The proposed solution combines ancient and modern physiognomy to understand the relationship between personality and facial features and to model a baseline to shape facial features. We compute a histogram of image by searching for threshold values to create a binary image in an adaptive way. The two-pass connected component method indicates the feature’s region. We encode the binary image to remove the noise point, so that the new connected image can provide a better result. According to our analysis of contours, we can locate facial features and classify them by means of a calculation method. The number of clusters is decided by a model and the facial feature contours are classified by using the k-means method. The validity of our method was tested on a face database and demonstrated by a comparative experiment.

Item Details

Item Type:Contribution to Refereed Journal
Keywords:facial feature extraction, facial feature recognition, physiognomy
Research Division:Information and Computing Sciences
Research Group:Graphics, augmented reality and games
Research Field:Computer graphics
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Huang, W (Dr Tony Huang)
ID Code:123667
Year Published:2017
Web of Science® Times Cited:4
Deposited By:Information and Communication Technology
Deposited On:2018-01-17
Last Modified:2018-12-13

Repository Staff Only: item control page