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The preprocessing routines consist of data interpolation and median filtering function that are applied to raw eye tracking to cope with problems in data quality.
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where ISR denotes the text region of the characters and MF denotes the median filter function.
Both the PTDS and the RePTDS can dynamically adapt their median filter functions to reduce the noise of the source images.
To reduce the effects of the noise in the source images, different median filter functions are also designed in the PTDS and the RePTDS individually.
MATLAB Image Processing Toolbox filtering functions are used for median filtering.
We used the MATLAB functions medfilt2 for median filtering and wiener2 for low-pass Wiener filtering to produce the results presented here.
In a complement to median filtering, McFarlane and Schofield [9] use a recursive filter to estimate median filtering to overcome the drawback of the previous model.
Last, for median filtering (Med).
Fig. 6 a Median filtering.
Median filtering was used for online measurements.
However, it is fragile to median filtering.
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