Face recognition under bad illumination conditions

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearch

Abstract

© Springer International Publishing Switzerland 2015. Accurate face recognition in variable illumination environments has attracted the attention of the researchers in recent years, because there are many applications in which these systems must operate under uncontrolled lighting conditions. To this end, several face recognition algorithms have been proposed which include an image enhancement stage before performing the recognition task. However, although the image enhancement stage may improve the performance, it also increases the computational complexity of face recognition algorithms. Because this fact may limit their use in some practical applications, recently some algorithms have been developed that intend to provide enough robustness under variable illumination conditions without requiring an image enhancement stage. Among them, the local binary pattern and eigenphasesbased schemes are two of the most successful ones. This paper presents an analysis of the recognition performance of these approaches under varying illumination conditions, with and without image enhancement preprocessing stages. Evaluation results show the robustness of both approaches when they are required to operate in illumination varying environments.
Original languageAmerican English
Title of host publicationFace recognition under bad illumination conditions
Pages506-516
Number of pages454
ISBN (Electronic)9783319226880
DOIs
StatePublished - 1 Jan 2015
EventCommunications in Computer and Information Science -
Duration: 1 Jan 2016 → …

Publication series

NameCommunications in Computer and Information Science
Volume532
ISSN (Print)1865-0929

Conference

ConferenceCommunications in Computer and Information Science
Period1/01/16 → …

Fingerprint

Face recognition
Image enhancement
Lighting
Computational complexity
image enhancement

Cite this

de los Santos, D. T., Nakano-Miyatake, M., Toscano-Medina, K., Sanchez-Perez, G., & Perez-Meana, H. (2015). Face recognition under bad illumination conditions. In Face recognition under bad illumination conditions (pp. 506-516). (Communications in Computer and Information Science; Vol. 532). https://doi.org/10.1007/978-3-319-22689-7_39
de los Santos, Daniel Toledo ; Nakano-Miyatake, Mariko ; Toscano-Medina, Karina ; Sanchez-Perez, Gabriel ; Perez-Meana, Hector. / Face recognition under bad illumination conditions. Face recognition under bad illumination conditions. 2015. pp. 506-516 (Communications in Computer and Information Science).
@inproceedings{4588758e44ed422c8c7e0046e2e8630d,
title = "Face recognition under bad illumination conditions",
abstract = "{\circledC} Springer International Publishing Switzerland 2015. Accurate face recognition in variable illumination environments has attracted the attention of the researchers in recent years, because there are many applications in which these systems must operate under uncontrolled lighting conditions. To this end, several face recognition algorithms have been proposed which include an image enhancement stage before performing the recognition task. However, although the image enhancement stage may improve the performance, it also increases the computational complexity of face recognition algorithms. Because this fact may limit their use in some practical applications, recently some algorithms have been developed that intend to provide enough robustness under variable illumination conditions without requiring an image enhancement stage. Among them, the local binary pattern and eigenphasesbased schemes are two of the most successful ones. This paper presents an analysis of the recognition performance of these approaches under varying illumination conditions, with and without image enhancement preprocessing stages. Evaluation results show the robustness of both approaches when they are required to operate in illumination varying environments.",
author = "{de los Santos}, {Daniel Toledo} and Mariko Nakano-Miyatake and Karina Toscano-Medina and Gabriel Sanchez-Perez and Hector Perez-Meana",
year = "2015",
month = "1",
day = "1",
doi = "10.1007/978-3-319-22689-7_39",
language = "American English",
isbn = "9783319226880",
series = "Communications in Computer and Information Science",
pages = "506--516",
booktitle = "Face recognition under bad illumination conditions",

}

de los Santos, DT, Nakano-Miyatake, M, Toscano-Medina, K, Sanchez-Perez, G & Perez-Meana, H 2015, Face recognition under bad illumination conditions. in Face recognition under bad illumination conditions. Communications in Computer and Information Science, vol. 532, pp. 506-516, Communications in Computer and Information Science, 1/01/16. https://doi.org/10.1007/978-3-319-22689-7_39

Face recognition under bad illumination conditions. / de los Santos, Daniel Toledo; Nakano-Miyatake, Mariko; Toscano-Medina, Karina; Sanchez-Perez, Gabriel; Perez-Meana, Hector.

Face recognition under bad illumination conditions. 2015. p. 506-516 (Communications in Computer and Information Science; Vol. 532).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearch

TY - GEN

T1 - Face recognition under bad illumination conditions

AU - de los Santos, Daniel Toledo

AU - Nakano-Miyatake, Mariko

AU - Toscano-Medina, Karina

AU - Sanchez-Perez, Gabriel

AU - Perez-Meana, Hector

PY - 2015/1/1

Y1 - 2015/1/1

N2 - © Springer International Publishing Switzerland 2015. Accurate face recognition in variable illumination environments has attracted the attention of the researchers in recent years, because there are many applications in which these systems must operate under uncontrolled lighting conditions. To this end, several face recognition algorithms have been proposed which include an image enhancement stage before performing the recognition task. However, although the image enhancement stage may improve the performance, it also increases the computational complexity of face recognition algorithms. Because this fact may limit their use in some practical applications, recently some algorithms have been developed that intend to provide enough robustness under variable illumination conditions without requiring an image enhancement stage. Among them, the local binary pattern and eigenphasesbased schemes are two of the most successful ones. This paper presents an analysis of the recognition performance of these approaches under varying illumination conditions, with and without image enhancement preprocessing stages. Evaluation results show the robustness of both approaches when they are required to operate in illumination varying environments.

AB - © Springer International Publishing Switzerland 2015. Accurate face recognition in variable illumination environments has attracted the attention of the researchers in recent years, because there are many applications in which these systems must operate under uncontrolled lighting conditions. To this end, several face recognition algorithms have been proposed which include an image enhancement stage before performing the recognition task. However, although the image enhancement stage may improve the performance, it also increases the computational complexity of face recognition algorithms. Because this fact may limit their use in some practical applications, recently some algorithms have been developed that intend to provide enough robustness under variable illumination conditions without requiring an image enhancement stage. Among them, the local binary pattern and eigenphasesbased schemes are two of the most successful ones. This paper presents an analysis of the recognition performance of these approaches under varying illumination conditions, with and without image enhancement preprocessing stages. Evaluation results show the robustness of both approaches when they are required to operate in illumination varying environments.

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84945951505&origin=inward

UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84945951505&origin=inward

U2 - 10.1007/978-3-319-22689-7_39

DO - 10.1007/978-3-319-22689-7_39

M3 - Conference contribution

SN - 9783319226880

T3 - Communications in Computer and Information Science

SP - 506

EP - 516

BT - Face recognition under bad illumination conditions

ER -

de los Santos DT, Nakano-Miyatake M, Toscano-Medina K, Sanchez-Perez G, Perez-Meana H. Face recognition under bad illumination conditions. In Face recognition under bad illumination conditions. 2015. p. 506-516. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-319-22689-7_39