  Skin lesion segmentation can be rather a challenging task owing to the
presence of artifacts, low contrast between lesion and boundary, color
variegation, fuzzy skin lesion borders and heterogeneous background in
dermoscopy images. In this paper, we propose a simple yet effective
saliency-based approach derived in the frequency and spatial domain to detect
pigmented skin lesion. Two color models are utilized for the construction of
these maps. We suggest a different metric for each color model to design map in
the spatial domain via color features. The map in the frequency domain is
generated from aggregated images. We adopt a separate fusion scheme to combine
salient features in their respective domains. Finally, two-phase saliency
integration scheme is devised to combine these maps using pixelwise
multiplication. Performance of the proposed method is assessed on PH2 and ISIC
2016 datasets. The outcome of the experiments suggests that the proposed scheme
generate better segmentation result as compared to state-of-the-art methods.
