Standard

Simple and robust facial portraits recognition under variable lighting conditions based on two-dimensional orthogonal transformations. / Forczmański, Paweł; Kukharev, Georgy; Shchegoleva, Nadezdha.

Image Analysis and Processing, ICIAP 2013 - 17th International Conference, Proceedings. PART 1. ed. 2013. p. 602-611 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8156 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Forczmański, P, Kukharev, G & Shchegoleva, N 2013, Simple and robust facial portraits recognition under variable lighting conditions based on two-dimensional orthogonal transformations. in Image Analysis and Processing, ICIAP 2013 - 17th International Conference, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 8156 LNCS, pp. 602-611, 17th International Conference on Image Analysis and Processing, ICIAP 2013, Naples, Italy, 9/09/13. https://doi.org/10.1007/978-3-642-41181-6_61

APA

Forczmański, P., Kukharev, G., & Shchegoleva, N. (2013). Simple and robust facial portraits recognition under variable lighting conditions based on two-dimensional orthogonal transformations. In Image Analysis and Processing, ICIAP 2013 - 17th International Conference, Proceedings (PART 1 ed., pp. 602-611). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8156 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-41181-6_61

Vancouver

Forczmański P, Kukharev G, Shchegoleva N. Simple and robust facial portraits recognition under variable lighting conditions based on two-dimensional orthogonal transformations. In Image Analysis and Processing, ICIAP 2013 - 17th International Conference, Proceedings. PART 1 ed. 2013. p. 602-611. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-41181-6_61

Author

Forczmański, Paweł ; Kukharev, Georgy ; Shchegoleva, Nadezdha. / Simple and robust facial portraits recognition under variable lighting conditions based on two-dimensional orthogonal transformations. Image Analysis and Processing, ICIAP 2013 - 17th International Conference, Proceedings. PART 1. ed. 2013. pp. 602-611 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

BibTeX

@inproceedings{8f87f7b9e8d8411889b4a4857f0856bf,
title = "Simple and robust facial portraits recognition under variable lighting conditions based on two-dimensional orthogonal transformations",
abstract = "The paper addresses the problem of face recognition for images registered in variable lighting, which is common for real-world conditions. Presented algorithm is based on orthogonal transformation preceded by simple transformations comprising of equalization of brightness gradients, removal of spatial low frequency spectral components and fusion of spectral features depending on average pixels intensity. Two types of transformations: 2DDCT (two-dimensional Discrete Cosine Transform) and 2DKLT (two-dimensional Karhunen-Loeve Transform) were investigated in order to find the most optimal algorithm setup. The results of experiments conducted on Yale B and Yale B+ datasets show that a quite simple algorithm is capable of successful recognition without high computing power demand, as opposite to several more sophisticated methods presented recently.",
keywords = "DCT, dimensionality reduction, face recognition, illumination compensation, PCA",
author = "Pawe{\l} Forczma{\'n}ski and Georgy Kukharev and Nadezdha Shchegoleva",
year = "2013",
month = oct,
day = "3",
doi = "10.1007/978-3-642-41181-6_61",
language = "English",
isbn = "9783642411809",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 1",
pages = "602--611",
booktitle = "Image Analysis and Processing, ICIAP 2013 - 17th International Conference, Proceedings",
edition = "PART 1",
note = "17th International Conference on Image Analysis and Processing, ICIAP 2013 ; Conference date: 09-09-2013 Through 13-09-2013",

}

RIS

TY - GEN

T1 - Simple and robust facial portraits recognition under variable lighting conditions based on two-dimensional orthogonal transformations

AU - Forczmański, Paweł

AU - Kukharev, Georgy

AU - Shchegoleva, Nadezdha

PY - 2013/10/3

Y1 - 2013/10/3

N2 - The paper addresses the problem of face recognition for images registered in variable lighting, which is common for real-world conditions. Presented algorithm is based on orthogonal transformation preceded by simple transformations comprising of equalization of brightness gradients, removal of spatial low frequency spectral components and fusion of spectral features depending on average pixels intensity. Two types of transformations: 2DDCT (two-dimensional Discrete Cosine Transform) and 2DKLT (two-dimensional Karhunen-Loeve Transform) were investigated in order to find the most optimal algorithm setup. The results of experiments conducted on Yale B and Yale B+ datasets show that a quite simple algorithm is capable of successful recognition without high computing power demand, as opposite to several more sophisticated methods presented recently.

AB - The paper addresses the problem of face recognition for images registered in variable lighting, which is common for real-world conditions. Presented algorithm is based on orthogonal transformation preceded by simple transformations comprising of equalization of brightness gradients, removal of spatial low frequency spectral components and fusion of spectral features depending on average pixels intensity. Two types of transformations: 2DDCT (two-dimensional Discrete Cosine Transform) and 2DKLT (two-dimensional Karhunen-Loeve Transform) were investigated in order to find the most optimal algorithm setup. The results of experiments conducted on Yale B and Yale B+ datasets show that a quite simple algorithm is capable of successful recognition without high computing power demand, as opposite to several more sophisticated methods presented recently.

KW - DCT

KW - dimensionality reduction

KW - face recognition

KW - illumination compensation

KW - PCA

UR - http://www.scopus.com/inward/record.url?scp=84884705275&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-41181-6_61

DO - 10.1007/978-3-642-41181-6_61

M3 - Conference contribution

AN - SCOPUS:84884705275

SN - 9783642411809

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 602

EP - 611

BT - Image Analysis and Processing, ICIAP 2013 - 17th International Conference, Proceedings

T2 - 17th International Conference on Image Analysis and Processing, ICIAP 2013

Y2 - 9 September 2013 through 13 September 2013

ER -

ID: 49225328