Due to the rapid advancement of auto-refractor technology, most optometry shops provide refraction services. Despite their speed and convenience, the measurement values provided by auto-refractors include a significant degree of error due to psychological and physical factors. Therefore, there is a need for repetitive testing to obtain a smaller mean error value. However, even repetitive testing itself might not be sufficient to ensure accurate measurements. Therefore, research on a method of measurement that can complement auto-refractor measurements and provide confirmation of refraction results needs to be conducted. The customized optometry model described herein can satisfy the above requirements. With existing technologies, using human eye measurement devices to obtain relevant individual optical feature parameters is no longer difficult, and these parameters allow us to construct an optometry model for individual eyeballs. They also allow us to compute visual images produced from the optometry model using the CODE V macro programming language before recognizing the diffraction effects visual images with the neural network algorithm to obtain the accurate refractive diopter. This study attempts to combine the optometry model with the back-propagation neural network and achieve a double check recognition effect by complementing the auto-refractor. Results show that the accuracy achieved was above 98% and that this application could significantly enhance the service quality of refraction.
© 2013 Optical Society of Korea
(200.0200) Optics in computing : Optics in computing
(330.5000) Vision, color, and visual optics : Vision - patterns and recognition
(330.4875) Vision, color, and visual optics : Optics of physiological systems
(330.7327) Vision, color, and visual optics : Visual optics, ophthalmic instrumentation
Original Manuscript: May 21, 2013
Revised Manuscript: July 19, 2013
Manuscript Accepted: July 22, 2013
Published: August 25, 2013
Lin-Song Chang and Bo-Wen Wu, "A New Application of Human Visual Simulated Images in Optometry Services," J. Opt. Soc. Korea 17, 328-335 (2013)
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