Additional Image Processing and Measurement
(4.1) for m ∈ (L K (n, i), L K (n, i) + p r9 ) and m i ∈ (1, p r9 ). The image L GK (m i , n) is shown in…
Introduction
Fig. 1.1 Image in the geometric coordinate system with points indicating brightness function domain pixels and squares representing detector sensors Fig. 1.2 Image in the screen coordinate system represented in the form…
Image Pre-processing
Fig. 2.1 Block diagram of the data acquisition and connection, through file conversion, with Matlab: a Corvis tonometer, b application OCULUS Corvis ST, c Matlab with the algorithm discussed in this…
Main Image Processing
The results are shown in Fig. 3.1. Fig. 3.1 Images L DSG , L DPG , L DCG and their zooms in the range m ∈ (1, 65), n ∈ (125, 146) obtained from the image…
Impact of Image Acquisition and Selection of Algorithm Parameters on the Results
(5.1) where: w m the measured feature value, w p the reference feature value calculated for the corneal image containing no noise. The results shown in Fig. 5.1 were obtained for…
Conclusions
© Springer International Publishing Switzerland 2016Robert KoprowskiImage Analysis for Ophthalmological DiagnosisStudies in Computational Intelligence63110.1007/978-3-319-29546-6_7 7. Conclusions Robert Koprowski1 (1) Division of Biomedical Computer Science, Faculty of Computer Science and Materials Science, University of Silesia, Sosnowiec,…
Summary of Measured Features
Feature Object Description w(1) Eyeball + cornea Contrast calculated on the basis of the GLCM analysis of the corneal texture w(2) Eyeball Maximum amplitude of the high harmonic of the eyeball reaction…
