We investigated a psychophysical similarity measure for selection of images similar to those of unknown masses on mammograms, which may assist radiologists in the distinction between benign and malignant masses. Sixty pairs of masses were selected from 1445 mass images prepared for this study, which were obtained from the Digital Database for Screening Mammography by the University of South Flo...

In this work, we are concerned with generating solutions of a class Convection–Diffusion–Reaction (CDR) equation from the another CDR through Darboux transformations. The method is elucidated by cases certain types reaction coefficients. We have also discussed briefly supersymmetric pairs equations connected similarity solutions.

This paper presents a novel Daubechies-based kernel Principal Component Analysis (PCA) method by integrating the Daubechies wavelet representation of palm images and the kernel PCA method for palmprint recognition. The palmprint is first transformed into the wavelet domain to decompose palm images and the lowest resolution subband coefficients are chosen for palm representation. The kernel PCA ...

The Pearson product-moment correlation coefficient is being used to evaluate the similarity of the high-performance liquid chromatographic fingerprints of traditional Chinese medicine (TCM) in China. It is confirmed that a large range of peak areas produced the wrong results. A new algorithm concerning weighted Pearson product-moment correlation coefficient is proposed in this article. The resu...

Partitioning objects into closely related groups that have different states allows to understand the underlying structure in the data set treated. Different kinds of similarity measure with clustering algorithms are commonly used to find an optimal clustering or closely akin to original clustering. Using shrinkage-based and rank-based correlation coefficients, which are known to be robust, the ...

This paper proposes an improved approach for content-based image retrieval in Discrete Cosine Transform domain. For each 4x4 DCT block, we calculate the statistical information of three groups of AC coefficients and propose to use these information to form the AC-Pattern and use DC coefficients of neighboring blocks to construct DC-Pattern. The histograms of these two patterns are constructed a...

Content based image retrieval has gained considerable attention in nowadays as a very useful tool in a plethora of applications. Web has become the most important application, because over 70% of it is devoted to images, and looking for a specific image is a really daunting task. The vast majority of these images are JPEG compressed. An extensive study of eighteen similarity measures used for i...

A crucial dimension of Content-based music management systems is their ability to compute automatically similarities between music titles. We propose a technique that allows users to find music titles that sound similar to songs they like. The technique relies on a modelling of the timbral characteristics of a music signal by distributions of Cepstrum coefficients. The resulting models are then...

This paper proposed a new spectral graph clustering model by casting the non-categorical spatial data sets into an undirected graph. Decomposition of the graph to Delaunay graph has been done for computational efficiency. All pair shortest path based model has been adapted for the creation of the underlying Laplacian matrix of the graph. The similarity among the nodes of the graph is measured b...

A set of clustering algorithms with proper weight on the formulation of distance which extend to mixed numeric and multiple binary values is presented. A simple matching and Jaccard coefficients are used to measure similarity between objects for multiple binary attributes. Similarities are converted to dissimilarities between  th and th objects. The performance of clustering algorithms with b...