We study the complexity of computing normalized information distance. introduce a hierarchy limit-computable functions by considering number oscillations. This is function version difference for sets. show that distance not in any level this hierarchy, strengthening previous nonapproximability results. As an ingredient to proof, we demonstrate conditional undecidability result about independenc...

disguised face recognition is a major challenge in the field of face recognition which has been taken less attention. therefore, in this paper a disguised face recognition algorithm based on local phase quantization (lpq) method and singular value decomposition (svd) is presented which deals with two main challenges. the first challenge is when an individual intentionally alters the appearance ...

An Euclidean graph associated with a molecule is defined by a weighted graph with adjacency matrix M = [dij], where for ij, dij is the Euclidean distance between the nuclei i and j. In this matrix dii can be taken as zero if all the nuclei are equivalent. Otherwise, one may introduce different weights for distinct nuclei. Balaban introduced some monster graphs and then Randic computed complexit...

This paper presents a boundary-based, topological shape descriptor: the distance profile. It is inspired by the LBP (= local binary pattern) scale space – a topological shape descriptor computed by a filtration with concentric circles around a reference point. For rigid objects, the distance profile is computed by the Euclidean distance of each boundary pixel to a reference point. A geodesic di...

By propagating a vector for each pixel, we show that nearly Euclidean distance maps can be produced quickly by a region growing algorithm using hierarchical queues. Properties of the propagation scheme are used to detect potentially erroneous pixels and correct them by using larger neighbourhoods, without significantly affecting the computation time. Thus, Euclidean distance maps are produced i...

We present a modified distance measure for use with distance transforms of anti-aliased, area sampled grayscale images of arbitrary binary contours. The modified measure can be used in any vector-propagation Euclidean distance transform. Our test implementation in the traditional SSED8 algorithm shows a considerable improvement in accuracy and homogeneity of the distance field compared to a tra...

It has been well established in the literature that the appropriate criterion for optimum trellis coded modulation design on the additive white Gaussian noise channel is maximization of the free Euclidean distance. We show here that when trellis coded modulation is used on a Rician fading channel with interleaving/deinterleaving, the design of the code for optimum performance is guided by other...

Anastasios Doulamis and Nikolaos Doulamis National Technical University of Athens, Electrical and Computer Engineering Department, 15773, Athens, Greece E-mail: [email protected] Abstract In this paper, we evaluate and investigate two main types of relevance feedback algorithms; the Euclidean and the correlation–based approaches. In the first case, we examine heuristic and optimal techniques, ...