biometric identification using visual system classification on handheld devices robb zucker
Post on 03-Jan-2016
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Overview
• The human eye and visual system• Classification potential based on visual system
abnormalities and pathology• Proposed experiment
Problems with the visual system
• The National Institute for Health (NIH) lists as many as 15 common causes for decreased visual acuity– Some physical abnormalities to the visual system
are inherent from birth (congenital)– Others, more commonly, occur with age
(presbyopia)
Light sensitivity
• Light sensitivity decreases as we age, as early as age 20. The intensity of illumination for light to just be seen is doubled every 13 years thereafter
• Due to:– resting diameter of pupil decreases (senile miosis)– Lens opacification– Vitreous humor opacification
The dress…
• Blue with black trim?
• White with gold trim?
Many factors effect how we see or perceive colors and shapes
The Experiment
• Create an app that forces users into difficult reading situations
• Capture both the light sensitivity rating and the orientation for each user
• Classification using K-Nearest Neighbor algorithm
Device sensors and controls
• INPUTS– Sensor.TYPE_LIGHT:Ambient light level in SI lux units– Sensor.TYPE_ORIENTATION:values[0]: Azimuthvalues[1]: Pitch, rotation around x-axisvalues[2]: Roll, rotation around the x-axis
• OUTPUTS– Settings.System.SCREEN_BRIGHTNESS
Effective Brightness
Correct backlight brightness value for ambient light passively illuminating the device
Expected results
For a given brightness level person A person B person C
Machine-Learning classification system based on k Nearest Neighbor (k-NN)
Application
• Additional security safeguard in a broader security system
• As a compliment to challenge question• As a compliment to user defined security icon
References• [1]Vision and Perception - Visual Processing • http://medicine.jrank.org/pages/1805/Vision-Perception-Visual-processing.html• [2] University of Calgary http://ucalgary.ca/pip369/mod9/aging/sensitivity• [3] Unar, J. A., Woo Chaw Seng, and Almas Abbasi. "A review of biometric
technology along with trends and prospects." Pattern recognition 47.8 (2014): 2673-2688.
• [4] News report via internet:• http://fox13now.com/2015/02/26/what-color-is-this-dress-viral-photo-stirs-
intense-internet-debate/• [5] Ross, Arun, and Anil Jain. Multimodal biometrics: An overview. na, 2004.• [6] National Institute of Health website:
http://www.nlm.nih.gov/medlineplus/ency/article/003029.htm• [7] Ullah, Abrar, et al. "Graphical and text based challenge questions for secure
and usable authentication in online examinations." Internet Technology and Secured Transactions (ICITST), 2014 9th International Conference for. IEEE, 2014.
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