Automatic Measurement of Eye Features Using Image Processing
Abstract
This paper presents a camera based eye anthropometric measurement system that automatically computes the pupil size, the inter-pupillary distance, palpebral fissure (PF) and the marginal reflex distance (MRD). These values are in general manually obtained in ophthalmologic exams using a millimetric ruler or gauges, and therefore are subject to errors. Besides improving the accuracy and reliability of the measurements, the system uses near-infrared (NIR) light that allows its use in different lighting conditions. A single NIR non-calibrated camera is used to measure both eyes at the same time. The eye features are extracted using image processing algorithms, and metric values are computed using a known chessboard pattern as reference. Experimental results demonstrate the real-time performance, accuracy and robustness of the method.References
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Douglas, T. (2004). Image processing for craniofacial landmark identification and measurement: a review of photogrammetry and cephalometry. Computerized Medical Imaging and Graphics, 28:401–409.
Holladay, J. (2008). The high cost of inaccurate pupillometry.
Morimoto, C., Koons, D., Amir, A., and Flickner, M. (2000). Pupil detection and tracking using multiple light sources. Image and Vision Computing, 18(4):331–336.
Yang, M., Kriegman, D., and Ahuja, N. (2002). Detecting faces in images: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 24(1):34–58.
Published
2009-07-20
How to Cite
MORIMOTO, Carlos Hitoshi.
Automatic Measurement of Eye Features Using Image Processing. In: BRAZILIAN SYMPOSIUM ON COMPUTING APPLIED TO HEALTH (SBCAS), 9. , 2009, Bento Gonçalves/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2009
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p. 2069-2076.
ISSN 2763-8952.
