We present a semi-automated image processing
method, the continuous maximum gradient (CMG) method, for
identifying the air–water interface in side-view digital images of
unidirectional water waves in a glass-walled laboratory wave flume.
In a manner similar to Canny edge detection, CMG exploits gradi ents in pixel intensity to identify the free surface, but also enforces
an additional streamline constraint. This latter step is necessary
to exclude signals from other features, such as wave gauges and
water droplets on the glass, which also exhibit large intensity
gradients. To demonstrate the performance and accuracy of CMG,
we first compare its detection results with independent wave gauge
measurements. The maximum difference in total spectral variance
was found to be approximately 4%, while quantitative error metrics
from a regression analysis yielded an R2 value of 0.997 for the
surface elevation time-series. We also compare the CMG detection
results with imagery data from existing literature where excellent
visual agreement is observed, confirming the broad applicability of
the CMG method. The employment of CMG facilitates free surface
measurements at a very high resolution (order of millimeters)
which is essential for capturing the spatio-temporal wave-field
evolution and obtaining instantaneous measurement of local wave
shape.