Asee peer logo

Methodology for Evaluating Statistical Equivalence in Face Recognition Using Live Subjects with Dissimilar Skin Tones

Download Paper |

Conference

2013 ASEE Annual Conference & Exposition

Location

Atlanta, Georgia

Publication Date

June 23, 2013

Start Date

June 23, 2013

End Date

June 26, 2013

ISSN

2153-5965

Conference Session

Interdisciplinary and Undergraduate Research in Engineering Technology

Tagged Division

Engineering Technology

Page Count

15

Page Numbers

23.901.1 - 23.901.15

Permanent URL

https://peer.asee.org/22286

Download Count

28

Request a correction

Paper Authors

biography

Rigoberto Chinchilla Eastern Illinois University

visit author page

Rigoberto Chinchilla, PhD in Integrated Engineering, Ohio University, is an Associate Professor of Applied Engineering and Technology at Eastern Illinois University (EIU) since 2004. His teaching and research interests include Quality Design, Biometric and Computer Security, Clean Technologies, Automation and Technology-Ethics. Dr. Chinchilla has been a Fulbright and a United Nations scholar, serves in numerous departmental and university committees at EIU and has been awarded several research grants in his career. Dr. Chinchilla can be reached at rchinchilla@eiu.edu.

visit author page

author page

Bryan G. Baker Eastern Illinois University

Download Paper |

Abstract

Methodology for Evaluating Statistical Equivalence in Face Recognition Using Live Subjects with Dissimilar Skin TonesThe general purpose of this study is to propose a methodology that can be employed in theapplication of facial recognition systems (FRS) to determine if a statistically significantdifference exists in a facial recognition system’s ability to match two dissimilar skin tonepopulations to their enrolled images. In particular, to test the face recognition system’s ability torecognize dark or light skin tone subjects. In addition to the direct comparison of results fromtwo different populations, this study uses a Box Behnken Design to examine four factorscommonly effecting facial recognition systems. The four factors tested were angle of the cameraviewing the subject; both horizontally to the left and right, as well as vertically, both above andbelow the subject’s line of sight. Additionally, the distance the subjects are from the camera, andthen intensity of the illumination on the subject. The experimentation was approached from theassumption that subjects are cooperative, following guidelines for proper enrollment andsubmission for matching. The experimentation of the four factors was conducted using two setsof three subjects. One set was dark skin tone males, and the second set was light skin tonemales. The results of the study showed a significance statistical difference at p = 0.05 levelbetween the two skin tones, with greater difficulty identifying the light skin tone test subjectsthan those with dark skin tone.

Chinchilla, R., & Baker, B. G. (2013, June), Methodology for Evaluating Statistical Equivalence in Face Recognition Using Live Subjects with Dissimilar Skin Tones Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. https://peer.asee.org/22286

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2013 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015