Abstract
In the real world, two non-intrusive biometric methods, namely face recognition and ear recognition, are interesting as they have flexibility in scanning the subject being tested. In particular, ear recognition is quite interesting as the ear pattern is stable in all emotions. This paper presents a novel way using block-based PCA to recognize ear even in case of partial occlusion. The other significance of the proposed method is that it can decide whether an input image is occluded or not. Conducted experiments, used a standard data set and shown that min–min fusion technique with city block distance metric is the apt ear recognition method when block-based PCA is used. The recognition rate with the proposed method is greater than 94%, and the equal error rate (EER) is less than 15% for a 25% occluded ear image.
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References
Abaza, A., Ross, A., Herbert, C., Harrison, M.A.F., Nixon, M.S.: A survey on ear biometrics. ACM Compu. Surv. 45(2) (2013)
Emersic, Z., Struc, V., Peer, P.: Ear recognition: more than a survey. Neurocomputing 255, 26–39 (2017)
Iannarelli, A.: Ear Identification, Forensic Identification Series. Paramount Publishing Company, Fremont, CA (1989)
Nejati, H., Zhang, L., Sim, T., Martinez-Marroquin, E., Dong, G.: Wonder ears: identification of identical twins from ear images. In: 21st International Conference on Pattern Recognition, pp. 1201–1204 (2012)
Chang, K., Bowyer, K.W., Sarkar, S., Victor, B.: Comparison and combination of ear and face images in appearance-based biometrics. IEEE Trans. Pattern Anal. Mach. Intell. 25(9), 1160–1165 (2003)
Turk, M., Pentland, A.: Face recognition using eigenfaces. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Maui, Hawaii, USA, pp. 586–591 (1991)
Fan, Z., Ni, M., Sheng, M., Wu, Z., Xu, B.: Principal component analysis integrating Mahalanobis distance for face recognition. In: Second International Conference on Robot, Vision and Signal Processing, pp. 89–92 (2013)
Cha, S.-H.: Comprehensive survey on distance/similarity measures between probability density functions. Int. J. Math. Models Methods Appl. Sci. 1(4), 300–307 (2007)
Golub, G.H., van Loan, C.F.: Matrix Computations, 3rd edn. John Hopkins University Press, Baltimore (1996)
Liu, L., Wang, Y., Wang, Q., Tan, T.: Fast principal component analysis using eigen space merging. IEEE Int. Conf. Image Process. (ICIP) 6, 457–460 (2007)
Tharwat, A., Ibrahim, A., Ali, H.A.: Personal identification using ear images based on fast and accurate principal component analysis. In: INFOS2012, pp. 56–59, May 2012
Aggarwal, C.C., Hinneburg, A., Keim, D.A.: On the surprising behavior of distance metrics in high dimensional space, pp. 420–434 (2001)
Querencias-uceta, D., Carmen, S.: Principal component analysis for ear-based biometric verification. IEEE conference, pp. 1–6 (2017)
Jain, A., Nandakumar, K., Ross, A.: Score normalization in multimodal biometric systems. J. Pattern Recogn. 38(12), 2270–2285 (2005)
Acknowledgements
This work is supported by University Grants Commission of India under the scheme—Minor Research Project No. MRP6023 Dated: 31. 10. 2016.
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Ratna Kumari, V., Rajesh Kumar, P., Srinivasa Kumar, S. (2019). Occluded Ear Recognition Using Block-Based PCA. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 898. Springer, Singapore. https://doi.org/10.1007/978-981-13-3393-4_58
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DOI: https://doi.org/10.1007/978-981-13-3393-4_58
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