Cellphone based Optometry using Hybrid Images
ISEF · 2016 Third Award
Overview
Measurement of refractive error of the eye requires expensive equipment which are generally not portable. My goal is to greatly simplify the process, reduce its cost and use no external hardware except a mobile device. This is done by using Hybrid Images, exploiting that the eye lens behaves like an optical low-pass filter. A Hybrid Image is a combination of low spacial frequencies of one image and high spacial frequencies of another. This creates an image that is perceived in one of two ways, as a function of the viewer’s distance or refractive error. My method requires a mobile device showing a series of hybrid images, to be held at a distance with the user giving simple inputs to the mobile device. This allows us to search for the standard deviation of the Gaussian point spread function, thereby calculating the myopic prescription. I also extend this to non-trivial point spread functions and estimate the Zernike coefficients, thereby calculating the wavefront and assigning prescription. In this project I discuss the approach and verify its accuracy.
Awards (2)
- Third Award of $1,000 $1,000
- Google: Award of $2,000 for best overall project in ocean science and exploration. $2,000
Competition history
- ISEF 2016
Resources
Related projects
ISEF · 2018
Smartphone-Controlled Portable Phoropter Powered by Variable Focal Length Liquid Lens
ISEF · 2026
OptiSkew: A Biophysical Approach for Self Assessment Eye Refractive Disorders (Year II)
ISEF · 2021
OCULI: Smartphone-based Screening Application and Low-Cost Lens that Identifies the Risk for Cataracts
ISEF · 2020
PanOculus: A Novel, Multifaceted Diagnostic Tool for Ocular Disease Powered by a Variable Focus Liquid Lens, Deep Learning, and Telemedicine Technology
ISEF · 2023
Skew-Axis Cylinder Lens Optical System: Novel Method of Clinical Optometry of Astigmatism, Characterization, Theoretical Modelling, and Implementation
ISEF · 2021
TeleAEye: Low-Cost Automated Eye Disease Diagnosis Using a Novel Smartphone Fundus Camera With AI
ISEF · 2022
Detecting Glaucoma From Retinal Fundus Images Using Machine Learning
ISEF · 2019
EyeSpy Diagnosis: Developing a Smartphone-Based Non-Invasive Intelligent Device and Application for the Accurate and Affordable Diagnosis of Eye Fundus Anomalies via Machine Learning
Closest projects by meaning, across every fair and year in the corpus.
Browse more like this
Source: Regeneron International Science and Engineering Fair