Skip to main content

2017 | OriginalPaper | Buchkapitel

A Lightweight Mamdani Fuzzy Controller for Noise Removal on Iris Images

verfasst von : Andrea Francesco Abate, Silvio Barra, Gianni Fenu, Michele Nappi, Fabio Narducci

Erschienen in: Image Analysis and Processing - ICIAP 2017

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The iris segmentation step is usually the most time consuming stage of biometric systems when dealing with non ideal conditions, which produce diverse noise factors during the acquisition. On the other side, it also represents a crucial step since poor removal of noise leads to degradation of recognition performance. In this work, a lightweight fuzzy-based solution has been explored. The goal is to propose a fast but reliable segmentation approach which preserves the original resolution of the iris images. The preliminary results obtained on a subset of MICHE dataset, confirmed both acceptable performance in terms of time consumption and good quality of segmentation mask suitable for matching purposes.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Abate, A.F., Barra, S., D’Aniello, F., Narducci, F.: Two-tier image features clustering for iris recognition on mobile. In: Petrosino, A., Loia, V., Pedrycz, W. (eds.) WILF 2016. LNCS, vol. 10147, pp. 260–269. Springer, Cham (2017). doi:10.1007/978-3-319-52962-2_23 CrossRef Abate, A.F., Barra, S., D’Aniello, F., Narducci, F.: Two-tier image features clustering for iris recognition on mobile. In: Petrosino, A., Loia, V., Pedrycz, W. (eds.) WILF 2016. LNCS, vol. 10147, pp. 260–269. Springer, Cham (2017). doi:10.​1007/​978-3-319-52962-2_​23 CrossRef
2.
Zurück zum Zitat Abate, A., Barra, S., Gallo, L., Narducci, F.: SKIPSOM: Skewness & kurtosis of iris pixels in Self Organizing Maps for iris recognition on mobile devices. In: 2016 23rd International Conference on Pattern Recognition (ICPR), Cancun, pp. 155–159 (2016). doi:10.1109/ICPR.2016.7899625 Abate, A., Barra, S., Gallo, L., Narducci, F.: SKIPSOM: Skewness & kurtosis of iris pixels in Self Organizing Maps for iris recognition on mobile devices. In: 2016 23rd International Conference on Pattern Recognition (ICPR), Cancun, pp. 155–159 (2016). doi:10.​1109/​ICPR.​2016.​7899625
3.
Zurück zum Zitat Abate, A.F., Barra, S., Gallo, L., Narducci, F.: Kurtosis and skewness at pixel level as input for SOM networks to iris recognition on mobile devices. Pattern Recogn. Lett. (2017) Abate, A.F., Barra, S., Gallo, L., Narducci, F.: Kurtosis and skewness at pixel level as input for SOM networks to iris recognition on mobile devices. Pattern Recogn. Lett. (2017)
4.
Zurück zum Zitat Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Süsstrunk, S.: Slic superpixels compared to state-of-the-art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intell. 34(11), 2274–2282 (2012)CrossRef Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Süsstrunk, S.: Slic superpixels compared to state-of-the-art superpixel methods. IEEE Trans. Pattern Anal. Mach. Intell. 34(11), 2274–2282 (2012)CrossRef
5.
Zurück zum Zitat Barra, S., Casanova, A., Narducci, F., Ricciardi, S.: Ubiquitous iris recognition by means of mobile devices. Pattern Recogn. Lett. 57, 66–73 (2015). Mobile Iris CHallenge Evaluation part I (MICHE I)CrossRef Barra, S., Casanova, A., Narducci, F., Ricciardi, S.: Ubiquitous iris recognition by means of mobile devices. Pattern Recogn. Lett. 57, 66–73 (2015). Mobile Iris CHallenge Evaluation part I (MICHE I)CrossRef
6.
Zurück zum Zitat Barra, S., De Marsico, M., Cantoni, V., Riccio, D.: Using mutual information for multi-anchor tracking of human beings. In: Cantoni, V., Dimov, D., Tistarelli, M. (eds.) BIOMET 2014. LNCS, vol. 8897, pp. 28–39. Springer, Cham (2014). doi:10.1007/978-3-319-13386-7_3 Barra, S., De Marsico, M., Cantoni, V., Riccio, D.: Using mutual information for multi-anchor tracking of human beings. In: Cantoni, V., Dimov, D., Tistarelli, M. (eds.) BIOMET 2014. LNCS, vol. 8897, pp. 28–39. Springer, Cham (2014). doi:10.​1007/​978-3-319-13386-7_​3
7.
Zurück zum Zitat Bowyer, K.W., Hollingsworth, K.P., Flynn, P.J.: A survey of iris biometrics research: 2008–2010. In: Bowyer, K.W., Burge, M.J. (eds.) Handbook of Iris Recognition. ACVPR, pp. 23–61. Springer, London (2016). doi:10.1007/978-1-4471-6784-6_2 CrossRef Bowyer, K.W., Hollingsworth, K.P., Flynn, P.J.: A survey of iris biometrics research: 2008–2010. In: Bowyer, K.W., Burge, M.J. (eds.) Handbook of Iris Recognition. ACVPR, pp. 23–61. Springer, London (2016). doi:10.​1007/​978-1-4471-6784-6_​2 CrossRef
8.
Zurück zum Zitat Castrillón-Santana, M., De Marsico, M., Nappi, M., Narducci, F., Proença, H.: Mobile iris challenge evaluation ii: results from the ICPR competition. In: International Conference on Pattern Recognition (2016) Castrillón-Santana, M., De Marsico, M., Nappi, M., Narducci, F., Proença, H.: Mobile iris challenge evaluation ii: results from the ICPR competition. In: International Conference on Pattern Recognition (2016)
10.
Zurück zum Zitat Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Semantic image segmentation with deep convolutional nets and fully connected CRFs. arXiv preprint arXiv:1412.7062 (2014) Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Semantic image segmentation with deep convolutional nets and fully connected CRFs. arXiv preprint arXiv:​1412.​7062 (2014)
11.
Zurück zum Zitat Daugman, J.: Statistical richness of visual phase information: update on recognizing persons by iris patterns. Int. J. Comput. Vis. 45(1), 25–38 (2001)CrossRefMATH Daugman, J.: Statistical richness of visual phase information: update on recognizing persons by iris patterns. Int. J. Comput. Vis. 45(1), 25–38 (2001)CrossRefMATH
13.
Zurück zum Zitat Daugman, J.G.: High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. Pattern Anal. Mach. Intell. 15(11), 1148–1161 (1993)CrossRef Daugman, J.G.: High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. Pattern Anal. Mach. Intell. 15(11), 1148–1161 (1993)CrossRef
14.
Zurück zum Zitat Du, Y., Arslanturk, E., Zhou, Z., Belcher, C.: Video-based noncooperative iris image segmentation. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 41(1), 64–74 (2011)CrossRef Du, Y., Arslanturk, E., Zhou, Z., Belcher, C.: Video-based noncooperative iris image segmentation. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 41(1), 64–74 (2011)CrossRef
15.
Zurück zum Zitat El-Zaart, A.: Skin images segmentation. J. Comput. Sci. 6(2), 217–223 (2010)CrossRef El-Zaart, A.: Skin images segmentation. J. Comput. Sci. 6(2), 217–223 (2010)CrossRef
16.
Zurück zum Zitat Haindl, M., Krupika, M.: Unsupervised detection of non-iris occlusions. Pattern Recogn. Lett. 57, 60–65 (2015). Mobile Iris CHallenge Evaluation part I (MICHE I)CrossRef Haindl, M., Krupika, M.: Unsupervised detection of non-iris occlusions. Pattern Recogn. Lett. 57, 60–65 (2015). Mobile Iris CHallenge Evaluation part I (MICHE I)CrossRef
17.
Zurück zum Zitat Hofbauer, H., Alonso-Fernandez, F., Wild, P., Bigun, J., Uhl, A.: A ground truth for iris segmentation. In: 2014 22nd International Conference on Pattern Recognition, pp. 527–532, August 2014 Hofbauer, H., Alonso-Fernandez, F., Wild, P., Bigun, J., Uhl, A.: A ground truth for iris segmentation. In: 2014 22nd International Conference on Pattern Recognition, pp. 527–532, August 2014
18.
Zurück zum Zitat Jarjes, A.A., Wang, K., Mohammed, G.J.: Improved greedy snake model for detecting accurate pupil contour. In: 2011 3rd International Conference on Advanced Computer Control, pp. 515–519, January 2011 Jarjes, A.A., Wang, K., Mohammed, G.J.: Improved greedy snake model for detecting accurate pupil contour. In: 2011 3rd International Conference on Advanced Computer Control, pp. 515–519, January 2011
19.
Zurück zum Zitat Jayalakshmi, S., Sundaresan, M.: A survey on iris segmentation methods. In: 2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering, pp. 418–423, February 2013 Jayalakshmi, S., Sundaresan, M.: A survey on iris segmentation methods. In: 2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering, pp. 418–423, February 2013
21.
Zurück zum Zitat Labati, R., Genovese, A., Piuri, V., Scotti, F.: Iris segmentation: state of the art and innovative methods. Intell. Syst. Ref. Libr. 37, 151–182 (2012)CrossRef Labati, R., Genovese, A., Piuri, V., Scotti, F.: Iris segmentation: state of the art and innovative methods. Intell. Syst. Ref. Libr. 37, 151–182 (2012)CrossRef
22.
Zurück zum Zitat Liang, Z., Wei, J., Zhao, J., Liu, H., Li, B., Shen, J., Zheng, C.: The statistical meaning of kurtosis and its new application to identification of persons based on seismic signals. Sensors 8(8), 5106–5119 (2008)CrossRef Liang, Z., Wei, J., Zhao, J., Liu, H., Li, B., Shen, J., Zheng, C.: The statistical meaning of kurtosis and its new application to identification of persons based on seismic signals. Sensors 8(8), 5106–5119 (2008)CrossRef
23.
Zurück zum Zitat Liu, Z., Li, X., Luo, P., Loy, C.C., Tang, X.: Semantic image segmentation via deep parsing network. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1377–1385 (2015) Liu, Z., Li, X., Luo, P., Loy, C.C., Tang, X.: Semantic image segmentation via deep parsing network. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1377–1385 (2015)
24.
Zurück zum Zitat Makinana, S., Malumedzha, T., Nelwamondo, F.V.: Iris image quality assessment based on quality parameters. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds.) ACIIDS 2014. LNCS, vol. 8397, pp. 571–580. Springer, Cham (2014). doi:10.1007/978-3-319-05476-6_58 CrossRef Makinana, S., Malumedzha, T., Nelwamondo, F.V.: Iris image quality assessment based on quality parameters. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds.) ACIIDS 2014. LNCS, vol. 8397, pp. 571–580. Springer, Cham (2014). doi:10.​1007/​978-3-319-05476-6_​58 CrossRef
25.
Zurück zum Zitat Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man Mach. Stud. 7(1), 1–13 (1975)CrossRefMATH Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man Mach. Stud. 7(1), 1–13 (1975)CrossRefMATH
27.
Zurück zum Zitat Pal, N.R., Pal, S.K.: A review on image segmentation techniques. Pattern Recogn. 26(9), 1277–1294 (1993)CrossRef Pal, N.R., Pal, S.K.: A review on image segmentation techniques. Pattern Recogn. 26(9), 1277–1294 (1993)CrossRef
28.
Zurück zum Zitat Proenca, H.: Iris recognition: on the segmentation of degraded images acquired in the visible wavelength. IEEE Trans. Pattern Anal. Mach. Intell. 32(8), 1502–1516 (2010)CrossRef Proenca, H.: Iris recognition: on the segmentation of degraded images acquired in the visible wavelength. IEEE Trans. Pattern Anal. Mach. Intell. 32(8), 1502–1516 (2010)CrossRef
29.
Zurück zum Zitat Rad, R.M., Attar, A., Atani, R.E.: A comprehensive layer based encryption method for visual data. Int. J. Sig. Process. Image Process. Pattern Recogn. 6(1), 37–48 (2013) Rad, R.M., Attar, A., Atani, R.E.: A comprehensive layer based encryption method for visual data. Int. J. Sig. Process. Image Process. Pattern Recogn. 6(1), 37–48 (2013)
30.
Zurück zum Zitat Ross, A., Shah, S.: Segmenting non-ideal irises using geodesic active contours. In: 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference, Baltimore, MD, pp. 1–6 (2006). doi:10.1109/BCC.2006.4341625 Ross, A., Shah, S.: Segmenting non-ideal irises using geodesic active contours. In: 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference, Baltimore, MD, pp. 1–6 (2006). doi:10.​1109/​BCC.​2006.​4341625
31.
Zurück zum Zitat Shah, S., Ross, A.: Iris segmentation using geodesic active contours. IEEE Trans. Inf. Forensics Secur. 4(4), 824–836 (2009)CrossRef Shah, S., Ross, A.: Iris segmentation using geodesic active contours. IEEE Trans. Inf. Forensics Secur. 4(4), 824–836 (2009)CrossRef
33.
Zurück zum Zitat Vatsa, M., Singh, R., Noore, A.: Improving iris recognition performance using segmentation, quality enhancement, match score fusion, and indexing. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 38(4), 1021–1035 (2008)CrossRef Vatsa, M., Singh, R., Noore, A.: Improving iris recognition performance using segmentation, quality enhancement, match score fusion, and indexing. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 38(4), 1021–1035 (2008)CrossRef
34.
Zurück zum Zitat Wan, Y., Clutter, M.L., Mei, B., Siry, J.P.: Assessing the role of U.S. timberland assets in a mixed portfolio under the mean-conditional value at risk framework. Forest Policy Econ. 50, 118–126 (2015)CrossRef Wan, Y., Clutter, M.L., Mei, B., Siry, J.P.: Assessing the role of U.S. timberland assets in a mixed portfolio under the mean-conditional value at risk framework. Forest Policy Econ. 50, 118–126 (2015)CrossRef
Metadaten
Titel
A Lightweight Mamdani Fuzzy Controller for Noise Removal on Iris Images
verfasst von
Andrea Francesco Abate
Silvio Barra
Gianni Fenu
Michele Nappi
Fabio Narducci
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-68548-9_9

Premium Partner