Mathematical morphology (MM) is a theory of non-linear operators used for the processing and analysis images. Morphological neural networks (MNNs) are whose neurons compute morphological operators. Dilations erosions elementary MM. From an algebraic point view, dilation erosion that commute respectively with supremum infimum operations. In this paper, we present linear dilation-erosion perceptr...

Triangle meshes are a popular representation of surfaces in computer graphics. Our aim is to detect feature on such surfaces. Feature regions distinguish themselves by high curvature. We are using discrete curvature analysis on triangle meshes to obtain curvature values in every vertex of a mesh. These values are then thresholded resulting in a so called binary feature vector. By adapting morph...

Time-frequency representations have been of great interest in the analysis and classification of non-stationary signals. The use of highly selective transformation techniques is a valuable tool for obtaining accurate information for studies of this type. The Wigner-Ville distribution has high time and frequency selectivity in addition to meeting some interesting mathematical properties. However...

In this paper, an approach to fuzzy mathematical morphology based on conjunctive uninorms is studied. It is proved that the most suitable conjunctive uninorms to be used in this framework are two special kinds of both, representable and idempotent uninorms. For these operators, it is proved that the most usual algebraic and morphological properties are preserved, such as, duality, monotonicity,...

Classical fuzzy mathematical morphology is one of the extensions of original binary morphology to greyscale morphology. Recently, this theory was further extended to interval-valued fuzzy mathematical morphology by allowing uncertainty in the grey values of the image and the structuring element. In this paper, we investigate the construction of increasing interval-valued fuzzy operators from th...

We propose a linear and a morphological approach for the characterization and segmentation of binary and digital random textures. We focus on descriptors at the level of pixels in images, combined with statistical learning to select and weight them. The approach is illustrated on simulations of textures patchworks, for which errors of classification can be evaluated.

Automatic road extraction from aerial images can be very helpful in traffic control and vehicle guidance systems. Most of the road detection approaches are based on image segmentation algorithms. Color-based segmentation is very sensitive to light changes and consequently the change of weather condition affects the recognition rate of road detection systems. In order to reduce the light change ...

We propose a multiresolution representation for maximum intensity projection (MIP) volume rendering, based on morphological pyramids which allow progressive refinement and have the property of perfect reconstruction. The pyramidal analysis and synthesis operators are composed of morphological erosion and dilation, combined with dyadic downsampling for analysis and dyadic upsampling for synthesi...

We recently proposed a multiresolution representation for maximum intensity projection (MIP) volume rendering based on morphological adjunction pyramids which allow progressive refinement and have the property of perfect reconstruction. In this algorithm the pyramidal analysis and synthesis operators are composed of morphological erosion and dilation, combined with dyadic downsampling for analy...