Segmentation methods, combining spectral and spatial information, are essential for analysis of multi-spectral images. In this article, we propose such a method based on statistical pattern recognition algorithms and a combined classifier approach. A set of experiments is presented with multi-spectral images of detergent laundry powders acquired by imaging cross-sections with scanning electron ...

detection of lymph nodes (lns) involvement by various pathological processes has great therapeutic and prognostic implications. the purpose of this study was to evaluate the usefulness and accuracy of triplex sonography (gray scale, color mapping and spectral doppler) in differentiating benign from malignant cervical lns. we used triplex sonography to evaluate 120 lns in 50 patients. the gray s...

Vector fields arise in many areas of computational science and engineering. For effective visualization of vector fields it is necessary to identify and extract important features inherent in the data, defined by filters that characterize certain patterns. Our prior approach for vector field analysis used the Clifford Fourier transform for efficient pattern recognition for vector field data def...

let $p$ be a prime number greater than three. in this paper, we prove the existence of a new family of homotopy elements in the stable homotopy groups of spheres $pi_{ast}(s)$ which is represented by $h_nh_mtilde{beta}_{s+2}in {rm ext}_a^{s+4, q[p^n+p^m+(s+2)p+(s+1)]+s}(mathbb{z}_p,mathbb{z}_p)$ up to nonzero scalar in the adams spectral sequence, where $ngeq m+2>5$, $0leq sext}_a^{s+2,q[(s+2)p...

Vector fields play an important role in many areas of computational physics and engineering. For effective visualization of vector fields it is necessary to identify and extract important features inherent in the data, defined by filters that characterize certain “patterns”. Our prior approach for vector field analysis used the Clifford Fourier transform for efficient pattern recognition for ve...

Past work has shown relationship between the ability to discriminate spectral patterns and measures of speech intelligibility. The purpose of this study was to investigate the ability of both children and young adults to discriminate static and dynamic spectral patterns, comparing performance between the two groups and evaluating within-group results in terms of relationship to speech-in-noise ...

In this paper we explore how to embed symbolic relational graphs with unweighted edges in a pattern-space. We adopt a graph-spectral approach. We use the leading eigenvectors of the graph adjacency matrix to de0ne eigenmodes of the adjacency matrix. For each eigenmode, we compute vectors of spectral properties. These include the eigenmode perimeter, eigenmode volume, Cheeger number, inter-mode ...

In this paper we explore how to represent object viewstructure by embedding the neighbourhood graphs of feature points in a pattern-space. We adopt a graph-spectral approach. We use the leading eigenvectors of the graph adjacency matrix to define clusters of nodes. For each cluster, we compute vectors of cluster properties. We embed these vectors in a pattern-space using two contrasting approac...

the daily record of geomagnetic variations at any world location typically shows a multitude of irregular changes in the field that represent the superposition of many spectral components whose amplitudes generally increase with increasing period. it has been a long established fact that variations in ground magnetic records are caused by the dynamo action in the upper atmosphere. these daily v...