Biomedical Engineering Reference
In-Depth Information
70
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10
0
0
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Fig. 11
Average vertical summation
amount of image data (comprises only lens and necessary surroundings). For next
image analysis, only necessary image data left that is rectangular ROI with lens and
part of iris (see Fig.
8
).
Second step of image analysis is determination of threshold for partial thresh-
olding [
20
]. For automatic setting of the threshold we choose another smaller
rectangular ROI on the border of lens and iris. In this ROI, program finds minimum
and maximum value and computes the average value that is set as threshold. Finally
partial thersholding for ROI is applied.
The third step is 8-neighborhood identification (for more details see [
20
]) that
controls and labels shapes in ROI and remove any possible undesirable objects or
areas except lens because of head and eye movements. Then the image analysis is
divided into two ways. The fist one is for convergence and the second one is for
accommodation.
For convergence analysis is necessary to find horizontal position of the center of
lens by following equation:
X
1
n
x
t
D
x
j
.j; k/ ;
j;k
where
n
is number of pixels,
x
j
is value
j
- position
(j,k)
pixel of the shape in
the picture,
n
is number of pixels in object,
x
t
is co-ordinate of the centre of lens
(COL). Next step determinates horizontal position of the 1st PI. First, we do average
vertical summation (Fig.
11
) that is vertical summation in pixel columns devided
by number of nonzero pixels in the same column. Then general difference with
weighting window that eliminates local extremes is applied twice:
