Text extraction is important step that strongly influences on the final recognition performance. This task is especially challenging in case of scene text which is characterized with wide set of degradations like complex backgrounds, uneven illumination, viewing angle, etc. In this paper we evaluated text extraction based on K-means clustering in HSI color space with chromatic distance and inte...

We investigated the perception of distance of visual targets with constant size and luminance presented between 20 and 120 cm from subjects' eyes. When retinal disparity cues were present, the subjects could reproduce very accurately the distance of a seen reference in this area. When only extraretinal information was available, distance perception was still correct for distances of 40 cm or le...

Recent experiments investigating the acoustic cues that underlie distance perception for nearby sources provide important insights into how distance cues can be incorporated into virtual auditory displays. Potential distance cues considered include overall level, reverberation, and interaural level differences. Perceptual research shows that the relative utility of these cues depends on the typ...

We consider approximate path-reporting distance oracles, distance labeling and labeled routing with extremely low space requirement, for general undirected graphs. For distance oracles, we show how to break the n log n space bound of Thorup and Zwick if approximate paths rather than distances need to be reported. For approximate distance labeling and labeled routing, we break the previously bes...

It is shown that space-time may possess the differentiability properties of manifolds as well as the ultraviolet finiteness properties of lattices. Namely, if a field's amplitudes are given on any sufficiently dense set of discrete points this could already determine the field's amplitudes at all other points of the manifold. The criterion for when samples are sufficiently densely spaced could ...

Metric information on similarities and distances in fold space is essential for quantitative work in structural bioinformatics and structural biology. Here we derive a suitable metric for protein structures from the fundamental axioms of similarity. Derivation of the metric also clarifies the relationship between the interrelated concepts of distance and similarity.

The distance preserving graph embedding problem is to embed vertices of a given weighted graph into points in 2-dimensional Euclidean space so that for each edge the distance between their corresponding endpoints is as close to the weight of the edge as possible. If the given graph is complete, that is, if distance constraints are given as a full matrix, then principal coordinate analysis can s...

We propose a labeling scheme for unweighted undirected graphs, that is an assignment of binary labels to vertices of a graph such that the distance between any pair of vertices can be decoded solely from their labels. Recently, Alstrup et al. [3] have shown a labeling scheme for sparse graphs with labels of size O( n D log D) where D = logn log m+n n . We present a simpler approach achieving si...