The purpose of this study is to find out if there is a relationship between parameter ofsegmentation and customer satisfaction, in order to find out the current parameter of segmentationin automobile industries In India researcher has gone through several published journal, books,magazines and companies data. The result shows that the most important factor for segmentation ofautomobile industri...

Introduction: The present study aimed to suggest an unsupervised method for the segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in axial magnetic resonance (MR) images of the abdomen. Materials and Methods: A self-organizing map (SOM) neural network was designed to segment the adipose tissue from other tissues in the MR images. The segmentation of SAT and VA...

This paper presents a novel approach to automatic classifying and identifying of tree leaves using image segmentation fusion. With the development of mobile devices and remote access, automatic plant identification in images taken in natural scenes has received much attention. Image segmentation plays a key role in most plant identification methods, especially in complex background images. Wher...

Segmentation of novel or dynamic objects in a scene, often referred to as background subtraction or foreground segmentation, is critical for robust high level computer vision applications such as object tracking, object classification and recognition. However, automatic realtime segmentation for robotics still poses challenges including global illumination changes, shadows, inter-reflections, c...

In this paper a novel approach for the registration and segmentation of dynamic contrast enhanced renal MR images is presented. This integrated method is motivated by the observation of the reciprocity between registration and segmentation in 4D time-series images. Fully automated Fourier-based registration with sub-voxel accuracy and semi-automated time-series segmentation were intertwined to ...

In this paper an improved approach for segmentation of brain tumor using MRI images has been presented. This approach consists of three steps, namely: preprocessing, segmentation and post processing. The preprocessing has been carried out using skull stripping and histogram equalization techniques. The region of interest is segmented by applying conventional Level Set method to the preprocessed...

This paper describes an unsupervised dynamic graphical model for morphological segmentation and bilingual morpheme alignment for statistical machine translation. The model extends Hidden Semi-Markov chain models by using factored output nodes and special structures for its conditional probability distributions. It relies on morpho-syntactic and lexical source-side information (part-of-speech, m...

This paper presents a novel unsupervised method for hierarchical topic segmentation. Lexical cohesion – the workhorse of unsupervised linear segmentation – is treated as a multi-scale phenomenon, and formalized in a Bayesian setting. Each word token is modeled as a draw from a pyramid of latent topic models, where the structure of the pyramid is constrained to induce a hierarchical segmentation...

we first describe how to “fuzzify” the estimated binary columns to create a [0,1]-valued column. werefer to this [0,1] -valued column as the soft segmentation column of the noisy spectrogram column.similarly to the collection of soft segmentation columns as the soft segmentation image, or simply asthe soft segmentation. the band-dependent posterior probability that the hard segmentation columnv...

introduction: virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. the segmentation of airways from ct images is a critical step for numerous virtual bronchoscopy applications. materials and methods: to overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy c-mean (fc-fcm), utilized...