Texture segmentation

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  • The field of digital image segmentation is continually evolving. Most recently, the advanced segmentation methods such as Template Matching, Spatial and Temporal ARMA Processes, Mean Shift Iterative Algorithm, Constrained Compound Markov Random Field (CCMRF) model and Statistical Pattern Recognition (SPR) methods form the core of a modernization effort that resulted in the current text. This new edition of "Advanced Image Segmentation" is but a reflection of the significant progress that has been made in the field of image segmentation in just the past few years.

    pdf126p kimngan_1 05-11-2012 31 6   Download

  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài:Research Article Multichannel Texture Segmentation Using Bamberger Pyramids

    pdf15p sting07 18-02-2012 16 2   Download

  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Optimized Multichannel Filter Bank with Flat Frequency Response for Texture Segmentation

    pdf11p dauphong20 11-03-2012 17 2   Download

  • In Chapter 1 we present in detail a framework for fully automated brain tissue classification. The framework consists of a sequence of fully automated state of the art image registration (both rigid and nonrigid) and image segmentation algorithms. Models of the spatial distribution of brain tissues are combined with models of expected tissue intensities, including correction of MR bias fields and estimation of partial voluming. We also demonstrate how this framework can be applied in the presence of lesions....

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  • Chapter 1 presents IVUS. Intravascular ultrasound images represent a unique tool to guide interventional coronary procedures; this technique allows to supervise the cross-sectional locations of the vessel morphology and to provide quantitative and qualitative information about the causes and severity of coronary diseases. At the moment, the automatic extraction of this kind of information is performed without taking into account the basic signal principles that guide the process of image generation....

    pdf661p echbuon 02-11-2012 39 11   Download

  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Conditional Random Field Approach to Unsupervised Texture Image Segmentation

    pdf12p dauphong14 11-02-2012 25 6   Download

  • EDGE DETECTION Changes or discontinuities in an image amplitude attribute such as luminance or tristimulus value are fundamentally important primitive characteristics of an image because they often provide an indication of the physical extent of objects within the image. Local discontinuities in image luminance from one level to another are called luminance edges. Global luminance discontinuities, called luminance boundary segments, are considered in Section 17.4.

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  • IMAGE SEGMENTATION Segmentation of an image entails the division or separation of the image into regions of similar attribute. The most basic attribute for segmentation is image luminance amplitude for a monochrome image and color components for a color image. Image edges and texture are also useful attributes for segmentation. The definition of segmentation adopted in this chapter is deliberately restrictive; no contextual information is utilized in the segmentation. Furthermore, segmentation does not involve classifying each segment....

    pdf37p doroxon 12-08-2010 63 3   Download


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