High Confidence Visual Recognition of Persons by a Test of Statistical Independence
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Summary
A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence, which implies a theoretical "cross-over" error rate of one in 131000 when a decision criterion is adopted that would equalize the false accept and false reject error rates.
- Type
- article
- Published
- 1993-11-01
- Cited by
- 3,720
- References
- 32
- Access
- Open access
- OpenAlex
- https://openalex.org/W2102796633
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:7234088
Keywords
Iris recognition, Artificial intelligence, Pattern recognition (psychology), Statistical hypothesis testing, Computer science
References
- Principe d'incertitude, bases hilbertiennes et algèbres d'opérateurs
- Smart cards: principles, practice, applications
- Physiology of the eye : clinical application
- Information in the zero crossings of bandpass signals
- Texture analysis — a survey
- A spatial filtering approach to texture analysis
- Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters.
- Localized texture processing in vision: analysis and synthesis in the Gaborian space
- On discriminating visual textures and images
- Two-dimensional spectral analysis of cortical receptive field profiles.
- A decision-making theory of visual detection.
- Texture analysis Anno 1983
- Automatic recognition and analysis of human faces and facial expressions: a survey
- The mathematical theory of communication
- Davson's Physiology of the Eye
- Textural Features for Image Classification
- Unsupervised texture segmentation using Gabor filters
- Machine identification of human faces
- Energy processing and coding factors in texture discrimination and image processing
- Statistical and structural approaches to texture
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- Person Identification Technique Using Human Iris Recognition
- Simple and secured access to networked home appliances via internet using SSL, BioHashing and single Authentication Server
- Photonic human identification based on deep learning of back scattered laser speckle patterns.
- IRIS DATA PARAMETRIZATION BY HERMITE PROJECTION METHOD
- Off-Angle Iris Recognition Utilizing Global ICA
- Iris recognition based on feature extraction
- Localizing non-ideal irises via Chan-Vese model and variation level set of active contours without re-initializing
- Iris Recognition Using Fuzzy Support Vector Machine With Several Kernels
- High Security Human Recognition System using Iris Images
- Efficient Identification Based on Human Iris Patterns
- Fourier Spectral of PalmCode as Descriptor for Palmprint Recognition
- Design of an iris verification system on embedded blackfin processor for access control application
- Searching for 'Fragile Bits' in Iris Codes Generated with Gabor Analytic Iris Texture Binary Encoder ⁄
- An efficient fusion strategy for multimodal biometric system
- Effect of Wavelet-transformed Iris Image Translation and Rotation on its Recognition Rate (An Experimental Approach using Haar Wavelet)
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