  The ability of the future low frequency component of the Square Kilometre
Array radio telescope (SKA-Low) to produce tomographic images of the redshifted
21-cm signal will enable direct studies of the evolution of the sizes and
shapes of ionized regions during the Epoch of Reionization. However, a reliable
identification of ionized regions in noisy interferometric data is not trivial.
Here, we introduce an image processing method known as superpixels for this
purpose. We compare this method with two other previously proposed ones, one
relying on a chosen threshold and the other employing automatic threshold
determination using the K-Means algorithm. We use a correlation test and
compare power spectra and bubble size distributions to show that the
superpixels method provides a better identification of ionized regions,
especially in the case of noisy data. We also describe some possible additional
applications of the superpixel method, namely the derivation of the ionization
history and constraints on the source properties in specific regions.
