In this paper, image compression using hybrid vector quantization scheme such as Multistage Vector Quantization (MSVQ) and Pyramid Vector Quantization (PVQ) are introduced. A combined MSVQ and PVQ are utilized to take advantages provided by both of them. In the wavelet decomposition of the image, most of the information often resides in the lowest frequency subband. MSVQ is applied to significa...

Current medical imaging systems provide excellent spatial resolution, high tissue contrast, and up to 65535 intensity levels. Thus, image processing techniques which aim to exploit the information contained in the images are necessary for using these images in computer-aided diagnosis (CAD) systems. Image segmentation may be defined as the process of parcelling the image to delimit different ne...

In addition to optimal conditions, invariant laws of Lorentz, parity and time reversal are imposed to find the relation between observables (spin rotation parameters) and bilinear combination of helicity amplitudes in pion-proton elastic scattering at 6.0 GeV/c. By normalizing the differential cross-section to unity, the magnitudes of helicity amplitudes and the angle between them are dete...

A kind of fuzzy neural networks FNNs based on adaptive pattern clustering and feature map APCFM is proposed to improve the property of the large delay and time varying of the sintering process. By using the density clustering and learning vector quantization LVQ , the sintering process is divided automatically into subclasses which have similar clustering center and labeled fitting number. Then...

In this note, we study the application of Q-algebras to strict quantization. In the case of a torus with a constant Poisson structure, our quantization gives the same star product as Rieffel [8]. And in the case of a 2-sphere, our quantization produces the fuzzy sphere.

Clustering is one of the most fundamental algorithms which have got huge applications especially in the area of Neuro Fuzzy Systems, Data Analysis, Linear Vector Quantization, Bio-informatics etc. Various approaches exist for clustering of data. A few of the commonly used approaches are K-Means clustering, Fuzzy C-Means Clustering, Subtractive Clustering, etc. Clustering may involve varied uses...

This study proposes a novel bacterial foraging swarm-based intelligent algorithm called the bacterial foraging particle swarm optimization (BFPSO) algorithm to design vector quantization (VQ)-based fuzzy-image compression systems. It improves compressed image quality when processing many image patterns. The BFPSO algorithm is an efficient evolutionary learning algorithm that manages complex glo...