The theory of hierarchical image representations has been well-established in Mathematical
Morphology, and provides a suitable framework to handle images through objects or regions …

In this paper we propose a machine learning approach to classify melanocytic lesions as
malignant or benign, using dermoscopic images. The lesion features used in the …

Image segmentation consists in creating partitions within an image into meaningful areas
and objects. It can be used in scene understanding and recognition, in fields like biology …

Deep convolutional neural networks can fully use the intrinsic relationship between features
and improve the separability of hyperspectral images, which has received extensive in …

Hierarchies, such as the tree of shapes, are popular representations for image simplification
and segmentation thanks to their multiscale structures. Selecting meaningful level lines …

Image segmentation can be defined as the detection of closed contours surrounding objects
of interest. Given a family of closed curves obtained by some means, a difficulty is to extract …

The Tree of Shapes (ToS) is a morphological, tree-based representation of an image,
translating the inclusion of its level lines. It features many invariants to image changes …

The tree of shapes is a self-dual tree-based image representation belonging to the field of
mathematical morphology. This representation is highly interesting since it is invariant to …

In this paper we propose a machine learning approach to classify melanocytic lesions in
malignant and benign from dermatoscopic images. The image database is composed of 433 …

Many methods relying on the morphological notion of shapes,(ie, connected components of
level sets) have been proved to be very useful for pattern analysis and recognition. Selecting …