Paper
8 February 2005 Research of adaptive threshold model and its application in iris tracking
Qijie Zhao, Dawei Tu, Rensan Wang, Daming Gao
Author Affiliations +
Abstract
The relationship between gray value of pixels and macro-information in image has been analyzed with the method in statistical mechanics. After simulating and curve fitting with the experiment data by statistic and regression method, an adaptive threshold model between average gray value and image threshold has been proposed in terms of Boltzmann statistics. On the other hand, the image characteristics around the eye region and the states of eyeball also have been analyzed, and an algorithm to extract the eye feature and locate its position on the image has been proposed, furthermore, another algorithm has been proposed to find the iris characteristic line and then to coordinate the iris center. At last, considering the cases of head gesture, different head position, and the opening state of eyes, some experiments have been respectively done with the function based on the adaptive threshold model and the designed algorithms in eye-gaze input human-computer interaction (HCI) system. The experiment results show that the algorithms can widely be applied in different cases, and real-time iris tracking can be performed with the adaptive threshold model and algorithms.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qijie Zhao, Dawei Tu, Rensan Wang, and Daming Gao "Research of adaptive threshold model and its application in iris tracking", Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); https://doi.org/10.1117/12.574203
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KEYWORDS
Eye models

Iris recognition

Detection and tracking algorithms

Data modeling

Eye

Head

Human-computer interaction

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