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Iris recognition biometric systems apply mathematical pattern-recognition techniques to images of the irises of an individual's eyes.. Iris recognition is an automated method of biometric identification that uses mathematical pattern-recognition techniques on video images of one or both of the irises of an individual's eyes, whose complex patterns are unique, stable, and can be seen from some ...
This comparison of optical character recognition software includes: OCR engines, that do the actual character identification; Layout analysis software, that divide scanned documents into zones suitable for OCR; Graphical interfaces to one or more OCR engines
Pages in category "Iris recognition" The following 8 pages are in this category, out of 8 total. This list may not reflect recent changes. * Iris recognition; C.
Tesseract is an optical character recognition engine for various operating systems. [5] It is free software, released under the Apache License. [1] [6] [7] Originally developed by Hewlett-Packard as proprietary software in the 1980s, it was released as open source in 2005 and development was sponsored by Google in 2006.
Iris and Face Recognition from Portal Video: the goal is to develop algorithms that recognize people from near infrared image sequences and high definition video sequences. The sequences will be acquired as people walk through a portal. Iris and Face Recognition from Controlled Images: the goal is to improve performance on iris and face imagery.
Facial recognition systems; GazoPa; Geometric feature learning; Gesture recognition; Image collection exploration; Image retrieval. Content-based image retrieval; Reverse image search; Image-based modeling and rendering; Integrated mail processing; Iris recognition; Machine vision; Mobile mapping; Navigation system components for: Autonomous ...
The following is a non-complete list of applications which are studied in computer vision. In this category, the term application should be interpreted as a high level function which solves a problem at a higher level of complexity. Typically, the various technical problems related to an application can be solved and implemented in different ways.
Object recognition, scene recognition 2014 [15] [16] J. Xiao et al. ImageNet: Labeled object image database, used in the ImageNet Large Scale Visual Recognition Challenge: Labeled objects, bounding boxes, descriptive words, SIFT features 14,197,122 Images, text Object recognition, scene recognition 2009 (2014) [17] [18] [19] J. Deng et al. LSUN