2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Iris Liveness Detection Using Fusion of Domain-Specific Multiple BSIF and DenseNet Features

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references39

          • Record: found
          • Abstract: not found
          • Article: not found

          Densely Connected Convolutional Networks

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            DAISY: an efficient dense descriptor applied to wide-baseline stereo.

            In this paper, we introduce a local image descriptor, DAISY, which is very efficient to compute densely. We also present an EM-based algorithm to compute dense depth and occlusion maps from wide-baseline image pairs using this descriptor. This yields much better results in wide-baseline situations than the pixel and correlation-based algorithms that are commonly used in narrow-baseline stereo. Also, using a descriptor makes our algorithm robust against many photometric and geometric transformations. Our descriptor is inspired from earlier ones such as SIFT and GLOH but can be computed much faster for our purposes. Unlike SURF, which can also be computed efficiently at every pixel, it does not introduce artifacts that degrade the matching performance when used densely. It is important to note that our approach is the first algorithm that attempts to estimate dense depth maps from wide-baseline image pairs, and we show that it is a good one at that with many experiments for depth estimation accuracy, occlusion detection, and comparing it against other descriptors on laser-scanned ground truth scenes. We also tested our approach on a variety of indoor and outdoor scenes with different photometric and geometric transformations and our experiments support our claim to being robust against these.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Deep Representations for Iris, Face, and Fingerprint Spoofing Detection

                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                IEEE Transactions on Cybernetics
                IEEE Trans. Cybern.
                Institute of Electrical and Electronics Engineers (IEEE)
                2168-2267
                2168-2275
                April 2022
                April 2022
                : 52
                : 4
                : 2370-2381
                Affiliations
                [1 ]Department of Computer Science and Engineering, DSPM International Institute of Information and Technology, Naya Raipur, India
                Article
                10.1109/TCYB.2020.3005089
                b74ac2ac-4e05-4d16-8d40-a6d01e0f5c8b
                © 2022

                https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-037

                History

                Comments

                Comment on this article