Dokumentenart: | Artikel | ||||
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Titel eines Journals oder einer Zeitschrift: | Soft Computing | ||||
Verlag: | SPRINGER | ||||
Ort der Veröffentlichung: | NEW YORK | ||||
Band: | 24 | ||||
Nummer des Zeitschriftenheftes oder des Kapitels: | 14 | ||||
Seitenbereich: | S. 3809-3827 | ||||
Datum: | 20 Juni 2019 | ||||
Zusätzliche Informationen (Öffentlich): | Issue Date March 2020 | ||||
Institutionen: | Sprach- und Literatur- und Kulturwissenschaften > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Informationswissenschaft (Prof. Dr. Udo Kruschwitz) Biologie und Vorklinische Medizin > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang | ||||
Identifikationsnummer: |
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Stichwörter / Keywords: | ALGORITHM; SIGNAL; Empirical mode decomposition; Green's function; Discrete cosine transform; Face recognition; Face verification; k-NN; SVM; Filters | ||||
Dewey-Dezimal-Klassifikation: | 000 Informatik, Informationswissenschaft, allgemeine Werke > 020 Bibliotheks- und Informationswissenschaft 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften, Biologie | ||||
Status: | Veröffentlicht | ||||
Begutachtet: | Ja, diese Version wurde begutachtet | ||||
An der Universität Regensburg entstanden: | Ja | ||||
Dokumenten-ID: | 43388 |
Zusammenfassung
Face recognition or verification remains a real challenge in the area of pattern recognition and image processing. The image acquisition process is a crucial step in which noise will inevitably be introduced, and in most cases this noise drastically decreases the accuracy of the classification rate of recognition systems, making them ineffective. This paper presents a novel approach to face ...
Zusammenfassung
Face recognition or verification remains a real challenge in the area of pattern recognition and image processing. The image acquisition process is a crucial step in which noise will inevitably be introduced, and in most cases this noise drastically decreases the accuracy of the classification rate of recognition systems, making them ineffective. This paper presents a novel approach to face recognition or verification, which increases the recognition rate in noisy environmental conditions. The latter is achieved by using the intrinsic face mode functions that result from applying a bi-dimensional empirical mode decomposition with Green's functions in tension to noisy images. Each image is individually decomposed, and noisy modes are discarded or filtered during reconstruction. Then, the extracted modes are used for classification purposes with canonical classifiers such as vector support machines or k-nearest neighbor classifiers. Experimental results show that this method achieves very stable results, almost independently of the amount of noise added to the image, due to the ability of decomposition to capture the noise in the first mode. Classification results using noisy images are at the same level as other algorithms proposed for the same databases but working on clean images and therefore are better than those obtained using classic image filters in noisy images. Moreover, unlike most of the available algorithms, the algorithm proposed in this paper is based on the input data (without the need to adjust parameters), making it transparent to the user. Finally, the proposed new approach achieves good results independently of the type of noise, the level of noise and the type of the database, which is not possible with other classical methods requiring parameter adjustment.
Metadaten zuletzt geändert: 29 Sep 2021 07:41