Description: 《Visual C++_MATLAB图像处理与识别实用案例精选》本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章，第1章－第6章是图像处理与识别的基础内容，包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别；第7章－第10章是图像处理与识别的工程实例，涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例，并结合理论算法，提供了大量MATLAB代码程序，以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章－第12章，是两个综合性较强的实例，分别足Visual C++实现的基于神经网络的文字识别系统和车牌定位系统。
本书附带的光盆给出了各个章节列举的实例的源代码，同时赠送了28个常用数字图像处理算法的Visual C++代码实现。光盘在下一次的上载中给出。
注 此为超星图书，请用超星阅读软件打开阅读。-"Visual C _MATLAB image processing and recognition of the practical case Showcase" the book systematically introduced the image processing and recognition of the basic tenets of the typical methods and practical skills. The book is divided into 12 chapters, Chapter 1-Chapter 6 of image processing and recognition of content, including images scientific overview MATLAB programming language images, image enhancement, image segmentation, image feature extraction and image recognition; Chapter 7-Chapter 10 of image processing and recognition of the engineering example, covering medical image processing, Character Recognition and self-guided trolley path recognition example, the combination of theory and algorithms, for a lot of MATLAB code procedures to help readers how to use MATLAB Platform: |
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Author:连接 |
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Description: 《Visual C++_MATLAB图像处理与识别实用案例精选》本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章，第1章－第6章是图像处理与识别的基础内容，包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别；第7章－第10章是图像处理与识别的工程实例，涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例，并结合理论算法，提供了大量MATLAB代码程序，以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章－第12章，是两个综合性较强的实例，分别足Visual C++实现的基于神经网络的文字识别系统和车牌定位系统。
本书附带的光盆给出了各个章节列举的实例的源代码，同时赠送了28个常用数字图像处理算法的Visual C++代码实现。光盘在下一次的上载中给出。
注 此为超星图书，请用超星阅读软件打开阅读。-"Visual C _MATLAB image processing and recognition of the practical case Showcase" the book systematically introduced the image processing and recognition of the basic tenets of the typical methods and practical skills. The book is divided into 12 chapters, Chapter 1-Chapter 6 of image processing and recognition of content, including images scientific overview MATLAB programming language images, image enhancement, image segmentation, image feature extraction and image recognition; Chapter 7-Chapter 10 of image processing and recognition of the engineering example, covering medical image processing, Character Recognition and self-guided trolley path recognition example, the combination of theory and algorithms, for a lot of MATLAB code procedures to help readers how to use MATLAB Platform: |
Size: 8505344 |
Author:连接 |
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Description: 基于Snake 模型的图像分割技术是近年来图像处理领域的研究热点之一。Snake 模型承载上层先验知识并融合
了图像的底层特征,针对医学图像的特殊性,能有效地应用于医学图像的分割中。本文对各种基于Snake 模型的改进算法和
进化模型进行了研究,并重点梳理了最新的研究成果,以利于把握基于Snake 模型的医学图像分割方法的脉络和发展方向。-Snake model based on image segmentation image processing technology in recent years one of the hot areas of research. Snake model bearing a priori knowledge of the upper and bottom of the convergence of image features, for the specificity of medical images can be effectively applied to medical image segmentation. In this paper, model-based Snake improved algorithm and evolutionary models were studied and focused on combing the latest research results, in order to grasp the Snake model based on medical image segmentation method of context and direction of development. Platform: |
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Author:赵希成 |
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Description: 本方法是对二维医学图像实现的Walsh变换，属于预处理范围，为下一步的图像分割，配准等打下基础-This method is the realization of two-dimensional medical images of the Walsh transform, belong to the scope of pre-treatment, for the next phase of image segmentation, registration, etc. to lay the groundwork Platform: |
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Author:hujin |
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Description: 图像分割是由图像处理到图像分析的关键步骤，涉及到计算机视觉技术的复杂问题。在医学图像方面，许多应用大都依赖于对图像中目标轮廓的准确提取。基于微分算子检测的方法几乎都对噪声较为敏感且不能保证得到连续的边缘，无法用于辨识和分析目标。由Kass提出的基于主动轮廓线的Snake模型[1]，用一个具有一定弹性的封闭曲线，在曲线自身形状约束力和由图像数据计算而来的外部力的共同作用下演化，来逼近目标边界，完成对图像的分割。
GVF snake VC++做的-Image segmentation by image processing to image analysis of the key steps involved in computer vision technology to complex problems. In medical images, many applications largely depends on the target images extracted contour accuracy. Based on the differential operator method of detecting almost all more sensitive to noise and can not guarantee that they will get straight edge, can not be used for target identification and analysis. Kass raised by the active contour based on the Snake model [1], with a certain flexibility of the closed curve in the curve shape their own binding and calculated by the image data from the external force under the joint effect of the evolution of the boundary to approximate the target , completion of the image segmentation. GVF snake VC++ Make the Platform: |
Size: 149504 |
Author:happynp |
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Description: 可用于医学图像处理的分水岭算法，可以输入黑白图像，生成彩色分割图像-Can be used for medical image processing of the watershed algorithm, can enter a black-and-white images, color segmentation image generated Platform: |
Size: 2048 |
Author:萧然 |
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Description: 先对图像进行开闭滤波，再使用分水岭分割图像，然后使用FCM对初始分割进行聚类，得到最终分割结果，对医学图像效果比较好。-First opening and closing image filtering, re-use watershed segmentation images, then use the FCM clustering of the initial partition, the final segmentation results, the medical image is better. Platform: |
Size: 680960 |
Author:xiaochunlei |
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Description: 图像二值化，用于医学图像处理。设定域值，将图像分成两色，以便于分割重建等操作。-Image Binarization for medical image processing. Domain value set will be divided into two color images in order to facilitate the segmentation reconstruction operation. Platform: |
Size: 384000 |
Author:zhanglu |
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Description: 这是一个3D医学图像处理软件，可以对图像进行分割和配准，对于三维和二维的医学图像都可以使用。-This is a 3D medical image processing software, you can image segmentation and registration for three-dimensional and two-dimensional medical images can be used. Platform: |
Size: 24842240 |
Author:gaojuan |
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Description: 用于检测3D血管图像的分叉点的一个程序，文件夹内还有说明文档，详细介绍了该程序的算法。是用itk库做的一个通用模板类，还有例子。- Branches of tubular structures (vasculature, trachea, neuron, etc.) in medical images are critical for the topology of these
structures. In many applications, It is very helpful to be able to decompose tubular structures and identify every individual
branch. For example, quantification of geometric vascular features, registration of trachea movement due to respiration, tracing of
neuron path. However, manual decomposition can be tedious, time-consuming, and subject to operator bias. In this paper, we
propose a novel method to decompose tubular structures automatically and describe how to implement it in ITK framework. The
input is a 2D/3D binary image that can be obtained from any segmentation techniques, as well as the junctions, which can be
generated automatically from our previously contributed ITK class: itk::JunctionDetectionFilter. The output will be
branches with their labels and their connection. There are only tw Platform: |
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Author:xrx |
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Description: “GrowCut” - Interactive Multi-Label N-D Image Segmentation By Cellular
Automata
Abstract
In this project we describe a novel algorithm for interactive multilabel
segmentation of N-dimensional images. Given a small number
of user-labelled pixels, the rest of the image is segmented automatically
by a Cellular Automaton. The process is iterative, as
the automaton labels the image, user can observe the segmentation
evolution and guide the algorithm with human input where the segmentation
is difficult to compute. In the areas, where the segmentation
is reliably computed automatically no additional user effort
is required. Results of segmenting generic photos and medical images
are presented. Our experiments show that modest user effort
is required for segmentation of moderately hard images. Platform: |
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Author:robin |
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Description: 本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章，第1章～第6章是图像处理与识别的基础内容，包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别；第7章～第10章是图像处理与识别的工程实例，涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例，并结合理论算法，提供了大量MATLAB代码程序，以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章～第12章，是两个综合性较强的实例，分别是Visual C++实现的基于神经网络的文字识别系统和车牌定位系统。 本书附带的光盘给出了各个章节列举的实例的源代码，同时赠送了28个常用数字图像处理算法的Visual C++代码实现。 本书讲解深入浅出，实例程序丰富，注重理论与实践相结合。本书可作为计算机应用、自动化、图像处理与模式识别、机电一体化专业的高年级本科生或研究生的参考书，也可供从事图像处理与识别的研究人员和工程技术人员阅读参考。-This book introduces the basic principles of image processing and recognition of the typical methods and practical skills . The book is divided into 12 chapters , Chapter 1- Chapter 6 is the basis of the content of image processing and recognition , including images scientific overview , MATLAB programming language images, image enhancement, image segmentation, image feature extraction and image recognition Chapter 7- Section Chapter 10 is a project example image processing and recognition , covering the medical image processing, character recognition and self- guided trolley path recognition example , the combination of theory and algorithms, for a lot of MATLAB code procedures to help readers learn how to use MATLAB language fast simulation , debugging and estimation methods algorithm. Chapter 11- Chapter 12 , are two examples of highly integrated , namely Visual C++ implementation based on neural network character recognition system and a license plate positioning system. The book Platform: |
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Author:朱朴宁 |
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Description: 在本文中，我们提出了一个
所谓自适应模糊-K-均值聚类新方法
（AFKM）聚类的图像分割这可能是
适用于一般的图像和/或特定的图象（即
医疗和显微图像），采用不同的拍摄的
消费类电子产品，即，例如，在
普通数码相机和CCD相机-In this paper, we present a
new clustering algorithm called Adaptive Fuzzy-K-means
(AFKM) clustering for image segmentation which could be
applied on general images and/or specific images (i.e.,
medical and microscopic images), captured using different
consumer electronic products namely, for example, the
common digital cameras and CCD cameras Platform: |
Size: 1701888 |
Author:张恺 |
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Description: region growing technique used for segmenting image...segmentation done in medical images to detect specific layer Platform: |
Size: 56320 |
Author:sujitha |
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Description: 医学CT图像处理系统，进行脑部CT图像分割。能够识别正常或是非正常的脑部CT图片。还包含所有的图像处理的基本处理的代码。-Medical CT image processing system for brain CT image segmentation . Able to identify normal or non- normal brain CT images . Also includes all of the basic processing of the image processing code.
Platform: |
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Author:zhaoyilin |
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Description: 本程序使用一个种子点进行区域增长，然后对图像进行分割，包括医学图像和自然图像，分割效果不错-The program uses a seed point for regional growth, and then it is used for the image segmentation, including medical and natural images, segmentation effect is good!! Platform: |
Size: 2440192 |
Author:陆青 |
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Description: Image segmentation plays a crucial role in many medical imaging applications by automating
or facilitating the delineation of anatomical structures and other regions of interest. We present herein
a critical appraisal of the current status of semi-automated and automated methods for the segmentation of
anatomical medical images. Platform: |
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Author:priya |
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Description: The picture division and the characteristic withdraw, matlab development environment
[all-cncut.tar.gz] - Foreigner to write matlab code for image segmentation, which is described in detail
[fenshuiling.rar] - Can be used for medical image processing of the watershed algorithm, can enter a black-and-white images, color segmentation image generated Platform: |
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Author:hicham |
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Description: This paper presents a novel active contour model in a variational level set formulation for simultaneous segmentation and
bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD)
with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of
image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances.
Then, we use the Gaussian distribution with bias field as a local region descriptor in level set formulation for segmentation(This paper presents a novel active contour model in a variational level set formulation for simultaneous segmentation and
bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD)
with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of
image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances.
Then, we use the Gaussian distribution with bias field as a local region descriptor in level set formulation for segmentation and
bias field correction of the images with inhomogeneous intensities. Therefore, image segmentation and bias field estimation are
simultaneously achieved by minimizing the level set formulation) Platform: |
Size: 2441216 |
Author:song86
|
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Search - image segmentation for medical images