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Sadeghi et al., 2017 - Google Patents

Geometrical analysis of machine learning security in biometric authentication systems

Sadeghi et al., 2017

Document ID
10040016994347421606
Author
Sadeghi K
Banerjee A
Sohankar J
Gupta S
Publication year
Publication venue
2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)

External Links

Snippet

Feature extraction and Machine Learning (ML) techniques are required to reduce high variability of biometric data in Biometric Authentication Systems (BAS) toward improving system utilization (acceptance of legitimate subjects). However, reduction in data variability …
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Classifications

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    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268—Feature extraction; Face representation
    • G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
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    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G06K9/52—Extraction of features or characteristics of the image by deriving mathematical or geometrical properties from the whole image
    • G06K9/527—Scale-space domain transformation, e.g. with wavelet analysis
    • G—PHYSICS
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    • G06K9/6279—Classification techniques relating to the number of classes
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    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6228—Selecting the most significant subset of features
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    • G06K9/6261—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation partitioning the feature space
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/00006—Acquiring or recognising fingerprints or palmprints
    • G06K9/00107—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
    • G06K9/00114—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger using image processing
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    • G06K9/6292—Fusion techniques, i.e. combining data from various sources, e.g. sensor fusion of classification results, e.g. of classification results related to same input data
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    • G—PHYSICS
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    • G06K9/00597—Acquiring or recognising eyes, e.g. iris verification

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