Vladimir Curic

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We propose a new distance measure, called Complement weighted sum of minimal distances, between finite sets in $${\mathbb Z }^n$$ and evaluate its usefulness for shape registration and matching. In this set distance the contribution of each point of each set is weighted according to its distance to the complement of the set. In this way, outliers and noise(More)
Spatially adaptive structuring elements adjust their shape to the local structures in the image, and are often defined by a ball in a geodesic distance or gray-weighted distance metric space. This paper introduces salience adaptive structuring elements as spatially variant structuring elements that modify not only their shape, but also their size according(More)
The problem of finding the digital convex fuzzy hull of a digital fuzzy set, whose support is made of some digital points (centroids) in Z 2 , is considered here. A region is DL−convex if, for any two pixels belonging to it, there exists a digital straight line between them, all of whose pixels belong to the region. An algorithm how to compute the DL−convex(More)
UNLABELLED SMeagol is a software tool to simulate highly realistic microscopy data based on spatial systems biology models, in order to facilitate development, validation and optimization of advanced analysis methods for live cell single molecule microscopy data. AVAILABILITY AND IMPLEMENTATION SMeagol runs on Matlab R2014 and later, and uses compiled(More)
In this paper we study set distances that are used in image processing. We propose a generalization of sum of minimal distances and show that its special case includes a metric by symmetric difference. The Hausdorff metric and the Chamfer matching distances are also closely related with the presented framework. In addition, we define the complement set(More)
—This paper introduces a new descriptor for characterizing and classifying the pixels of texture images by means of General Adaptive Neighborhoods (GANs). The GAN of a pixel is a spatial region surrounding it and fitting its local image structure. The features describing each pixel are then region-based and intensity-based measurements of its corresponding(More)
We present two different extensions of the Sum of minimal distances and the Complement weighted sum of minimal distances to distances between fuzzy sets. We evaluate to what extent the proposed distances show monotonic behavior with respect to increasing translation and rotation of digital objects, in noise free, as well as in noisy conditions. Tests show(More)