Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/10553
Title: Secure Multimodal Access with 2D and 3D Ears
Authors: Ganapathi, Iyyakutti Iyappan
Prakash, Surya
Ali, Syed Sadaf
Keywords: 3d descriptor;3d ear;Co-registered ear image;Feature descriptors;Feature keypoint;Keypoints;Multi-modal techniques;Multimodal access;Secure access;Verification/identification;Probes
Issue Date: 2021
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: Ganapathi, I. I., Prakash, S., & Ali, S. S. (2021). Secure Multimodal Access with 2D and 3D Ears. In P. Kumar & A. K. Singh (Eds.), Machine Learning for Intelligent Multimedia Analytics (Vol. 82, pp. 1–20). Springer Singapore. https://doi.org/10.1007/978-981-15-9492-2_1
Abstract: This chapter introduces a multimodal technique that uses 2D and 3D ear images for secure access. The technique uses 2D-modality to identify keypoints and 3D-modality to describe keypoints. Upon detection and mapping of keypoints into 3D, a feature descriptor vector is computed around each mapped keypoint in 3D. We perform a two-stage, coarse and fine alignment to fit the 3D ear image of the probe to the 3D ear image of the gallery. The probe and gallery image keypoints are compared using feature vectors, where very similar keypoints are used as coarse alignment correspondence points. Once the ear pairs are matched fairly closely, the entire data is finely aligned to compute the matching score. A detailed systematic analysis using a large ear database has been carried out to show the efficiency of the technique proposed. © 2021, Springer Nature Singapore Pte Ltd.
URI: https://doi.org/10.1007/978-981-15-9492-2_1
https://dspace.iiti.ac.in/handle/123456789/10553
ISSN: 2197-6503
Type of Material: Book Chapter
Appears in Collections:Department of Computer Science and Engineering

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