- Tytuł:
- Noise robust illumination invariant face recognition via bivariate wavelet shrinkage in logarithm domain
- Autorzy:
-
Chen, Guang Yi
Krzyżak, Adam
Duda, Piotr
Cader, Andrzej - Powiązania:
- https://bibliotekanauki.pl/articles/2147140.pdf
- Data publikacji:
- 2022
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
face recognition
dual-tree complex wavelet transforms
DTCWT
collaborative representation-based classifier
CRC
invariant features
pattern recognition
computer vision - Opis:
- Recognizing faces under various lighting conditions is a challenging problem in artificial intelligence and applications. In this paper we describe a new face recognition algorithm which is invariant to illumination. We first convert image files to the logarithm domain and then we implement them using the dual-tree complex wavelet transform (DTCWT) which yields images approximately invariant to changes in illumination change. We classify the images by the collaborative representation-based classifier (CRC). We also perform the following sub-band transformations: (i) we set the approximation sub-band to zero if the noise standard deviation is greater than 5; (ii) we then threshold the two highest frequency wavelet sub-bands using bivariate wavelet shrinkage. (iii) otherwise, we set these two highest frequency wavelet sub-bands to zero. On obtained images we perform the inverse DTCWT which results in illumination invariant face images. The proposed method is strongly robust to Gaussian white noise. Experimental results show that our proposed algorithm outperforms several existing methods on the Extended Yale Face Database B and the CMU-PIE face database.
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 3; 169--180
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki