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Ear Biometrics in 2D and 3D: Localization and Recognition by Surya Prakash, Phalguni Gupta PDF

By Surya Prakash, Phalguni Gupta

ISBN-10: 9812873740

ISBN-13: 9789812873743

ISBN-10: 9812873759

ISBN-13: 9789812873750

This booklet offers the cutting-edge strategies and up to date examine development on Ear Biometrics. one of the quite a few physiological characteristics, the explanations for the ear to realize a lot cognizance in recent times are many folds. it's been came upon to be a competent biometrics for human verification and identity. Ears are remarkably constant and in contrast to face, it doesn't swap form with diverse expressions or age, and stay fastened in the midst of the facet of the pinnacle opposed to a predictable historical past. The booklet includes figures, tables and plots to demonstrate the recommendations in a simple and lucid demeanour. The e-book additionally offers an intensive literature at the topic, the place readers benefit from receiving all of the correct fabric at one position in a really finished demeanour. This ebook caters scholars, teachers, researchers, practitioners who're drawn to the sector of Ear Biometrics and its functions in face acceptance and security.

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Extra info for Ear Biometrics in 2D and 3D: Localization and Recognition

Sample text

However, there may exist few more places in the profile face where due to noise a convex hull of one edge may intersect that of other edges and give rise to a large connected component. Hence, each connected component in the edge connectivity graph which has two or more vertices is considered as a probable candidate to represent the ear. Any connected component having single vertex can be straightaway removed from the graph as it cannot represent the ear. Let K = {K 1 , K 2 , . . , K m } be the set of connected components of graph G where each component has two or more number of vertices.

2008. Human ear recognition by computer. Springer. 3. Iannarelli, A. 1989. Ear identification. Fremont California: Paramount Publishing Company. 4. Chang, Kyong, Kevin W. Bowyer, Sudeep Sarkar, and Barnabas Victor. 2003. Comparison and combination of ear and face images in appearance-based biometrics. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(9): 1160–1165. 5. W. Bowyer. 2007. Biometric recognition using 3D ear shape. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(8): 1297–1308.

2] have used force field technique to get the ear location. The technique claims that it does not require exact ear localization for ear recognition. However, it is only applicable when a small background is present in ear image. In [3], Yan and Bowyer have used manual technique based on two-line landmark to detect ear where one line is taken along the border between the ear and the face while other line is considered from the top of the ear to the bottom. The 2D ear localization technique proposed by Alvarez et al.

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Ear Biometrics in 2D and 3D: Localization and Recognition by Surya Prakash, Phalguni Gupta


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