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020 _a9789813299450
_9978-981-32-9945-0
024 7 _a10.1007/978-981-32-9945-0
_2doi
050 4 _aTA1501-1820
050 4 _aTA1634
072 7 _aUYT
_2bicssc
072 7 _aCOM016000
_2bisacsh
072 7 _aUYT
_2thema
082 0 4 _a006
_223
100 1 _aRahman, S. M. Mahbubur.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aOrthogonal Image Moments for Human-Centric Visual Pattern Recognition
_h[electronic resource] /
_cby S. M. Mahbubur Rahman, Tamanna Howlader, Dimitrios Hatzinakos.
250 _a1st ed. 2019.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2019.
300 _aXII, 149 p. 58 illus., 42 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aCognitive Intelligence and Robotics,
_x2520-1964
505 0 _a1 Introduction -- 2 Image Moments -- 3 Face Recognition -- 4 Expression Recognition -- 5 Fingerprint Classification -- 6 Iris Recognition -- 7 Hand Gesture Recognition -- 8 Conclusion.
520 _aInstead of focusing on the mathematical properties of moments, this book is a compendium of research that demonstrates the effectiveness of orthogonal moment-based features in face recognition, expression recognition, fingerprint recognition and iris recognition. The usefulness of moments and their invariants in pattern recognition is well known. What is less well known is how orthogonal moments may be applied to specific problems in human-centric visual pattern recognition. Unlike previous books, this work highlights the fundamental issues involved in moment-based pattern recognition, from the selection of discriminative features in a high-dimensional setting, to addressing the question of how to classify a large number of patterns based on small training samples. In addition to offering new concepts that illustrate the use of statistical methods in addressing some of these issues, the book presents recent results and provides guidance on implementing the methods. Accordingly, it will be of interest to researchers and graduate students working in the broad areas of computer vision and visual pattern recognition.
650 0 _aImage processing
_xDigital techniques.
650 0 _aComputer vision.
650 1 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
700 1 _aHowlader, Tamanna.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aHatzinakos, Dimitrios.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789813299443
776 0 8 _iPrinted edition:
_z9789813299467
776 0 8 _iPrinted edition:
_z9789813299474
830 0 _aCognitive Intelligence and Robotics,
_x2520-1964
856 4 0 _uhttps://doi.org/10.1007/978-981-32-9945-0
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c173305
_d173305