Multimodal Biometrics Based on Near-Infrared Face Recognition in .NET

Render QR in .NET Multimodal Biometrics Based on Near-Infrared Face Recognition
9
scan qr code iso/iec18004 in .net
Using Barcode Control SDK for VS .NET Control to generate, create, read, scan barcode image in VS .NET applications.
Multimodal Biometrics Based on Near-Infrared Face Recognition
Qr Barcode drawer in .net
use vs .net qr code iso/iec18004 encoder tointegrate qr in .net
Figure 9.9. ROC curves for score fusion of NIR face and VL face.
recognizing qr code 2d barcode for .net
Using Barcode decoder for Visual Studio .NET Control to read, scan read, scan image in Visual Studio .NET applications.
six fusion methods and two single modalities, and Figure 9.9 shows the corresponding ROC curves. 9.4.2.2 Results for NIR Face and Iris Fusion
Bar Code barcode library for .net
Using Barcode reader for .net framework Control to read, scan read, scan image in .net framework applications.
In this section we use the AdaBoost classi er trained from the above experiment for NIR face recognition and construct iris classi er using the method in reference 31. The method to choose R is the same as fusion of NIR and VL face and the determined value of R is 3 for the NIR face and iris fusion. Since the face matching scores and iris matching scores are not in common domain, we need to normalize the scores from different modalities rst. Three common normalization methods min-max, Z-score, and tanh-score normalization are used and compared in the experiments. Table 9.3 shows the match results for six fusion methods and three single modalities with three different normalization methods, and Figure 9.9 shows the corresponding ROC curves with different normalization methods.
Bar Code barcode library on .net
use visual .net barcode maker toreceive bar code in .net
Discussions
Control qr bidimensional barcode image on c#.net
use visual .net qr code iso/iec18004 development toreceive quick response code in .net c#
From the experimental results, we can observe that in most cases, fusion of NIR with VL faces and fusion of NIR face with iris modality can improve the recognition
Qr Bidimensional Barcode drawer in .net
using web tointegrate qr codes for asp.net web,windows application
Table 9.3. GAR and EER for Score Fusion of NIR Face and Iris GAR(%) (FAR = 0.1%) Min Max PSM LDA SUM MIN MAX NIR face Left-iris Right-iris 98.9 98.6 98.3 88.8 91.4 88.2 91.1 91.8 Z-Score 98.9 98.6 97.8 97.7 92.0 88.2 91.1 91.8 Tanh 98.9 98.4 97.8 97.7 92.0 88.2 91.1 91.8 Min Max 0.39 0.44 0.67 1.61 5.34 1.59 3.99 5.08 EER(%) Z-Score 0.39 0.52 1.19 0.46 5.52 1.59 3.99 5.08 Tanh 0.39 0.53 1.20 0.46 5.53 1.59 3.99 5.08
Control qr barcode image on vb
use .net framework qr-codes integrating toaccess denso qr bar code with vb.net
Figure 9.10. ROC curves for score fusion of NIR face and iris with three normalization methods:
Attach code-128c on .net
generate, create ansi/aim code 128 none on .net projects
((a) min max, (b) Z-score, (c) Tanh.)
Use pdf-417 2d barcode for .net
use .net framework pdf 417 encoder touse pdf417 2d barcode for .net
9
EAN 128 barcode library with .net
using visual studio .net crystal toinsert ean / ucc - 13 for asp.net web,windows application
Multimodal Biometrics Based on Near-Infrared Face Recognition
USD-8 barcode library for .net
using barcode maker for visual .net crystal control to generate, create "usd8 image in visual .net crystal applications.
accuracy compared to any single modality performance, which proves the effectiveness of multimodal biometrics. The learning-based fusion methods such as LDA and PSM achieve better results than other methods, and the PSM-based method has achieved the best performance in all the cases. In the case of fusion of NIR and VL faces, the genuine accept rate (GAR) increases from 90.1% (NIR face) to 93.2%; and in the case of fusion of NIR face and iris biometric, the GAR increases from 88.2% (NIR face) to 98.9%. Moreover, comparing the results in NIR face and iris fusion, it can be seen that the PSM- and LDA-based methods have similar results with different score normalization methods, while the performance of some of the conventional methods such as min or max rule may uctuate a little large. This indicates that the learning-based PSM and LDA methods are more robust to normalization methods and hence more suitable in practical applications.
Code 3/9 barcode library on none
Using Barcode Control SDK for None Control to generate, create, read, scan barcode image in None applications.
CONCLUSIONS
In this chapter we explore synergies of NIR + VL faces and NIR face + iris by proposing an NIR face-based approach for multibiometrics. The NIR face is fused with VL face or iris in a natural way. This approach takes the advantages of recent progress in NIR face recognition, and it further improves the performance of biometric systems. Experimental results show that both the fusion of NIR + VL face and NIR face + iris can signi cantly improve the system performance in real databases. The learning-based methods such as LDA- and PSM-based fusion achieve the best results and are robust to score normalization, thus they are practical in real applications.
UCC - 12 creator in .net c#
generate, create upc code none for visual c#.net projects
ACKNOWLEDGMENTS
decode barcode in .net
Using Barcode decoder for .NET Control to read, scan read, scan image in .NET applications.
This work was supported by the following funding resources: National Natural Science Foundation Project #60518002, National Science and Technology Supporting Platform Project #2006BAK08B06, National 863 Program Projects #2006AA01Z192 and #2006AA01Z193, Chinese Academy of Sciences 100 people project, and the AuthenMetric Collaboration Foundation.
UPC A barcode library in .net
using barcode implement for local reports rdlc control to generate, create upc code image in local reports rdlc applications.
REFERENCES
3 Of 9 Barcode integration for .net
generate, create code 39 none for .net projects
1. A. K. Jain, R. M. Bolle, and S. Pankanti, Biometrics: Personal Identi cation in Networked Society, Kluwer, Norwell, MA, 1999. 2. S. Z. Li, R. Chu, S. C. Liao, and L. Zhang, Illumination invariant face recognition using near-infrared images, IEEE Trans. Pattern Anal. Mach. Intell. 29(4):627 639, 2007. 3. S. Z. Li, L. Zhang, S. C. Liao, X. X. Zhu, R. F. Chu, M. Ao, and R. He. A near-infrared image based face recognition system, in Proceedings of 7th IEEE International Conference Automatic Face and Gesture Recognition (FG-2006), Southampton, UK, April 10 12, 2006, pp. 455 460. 4. S. Z. Li, R. F. Chu, M. Ao, L. Zhang, and R. He, Highly accurate and fast face recognition using near infrared images, in Proceedings of IAPR International Conference on Biometric (ICB-2006), Hong Kong, January 2006, pp. 151 158. 5. J. Kittler, M. Hatel, R. P. W. Duin, and J. Matas, On combining classi ers, IEEE Trans. Pattern Anal. Mach. Intell. 20(3):226 239, 1998.
Receive ucc - 12 for visual basic.net
using barcode generating for web pages crystal control to generate, create ean / ucc - 14 image in web pages crystal applications.
Control ean13 data in office excel
to generate ean-13 supplement 5 and ean-13 data, size, image with excel spreadsheets barcode sdk