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本书主要论述了智能图像处理技术,系统介绍了智能图像处理技术的有代表性的思想、算法与应用，跟踪了图像处理技术的发展前沿。全书共分为15章，重点讨论了图像边缘检测、图像分割、图像特征分析、图像配准、图像融合、图像分类、图像识别、基于内容的图像检索与图像数字水印。此外，为了内容的完整性，本书还介绍了图像预处理技术，如图像采集、图像变换、图像增强、图像恢复、图像编码与压缩-This book focuses on intelligent image processing technologies, sy
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使用Weka分析环境开发的基于Java的图像分割及基于内容检索程序，分割采用最小生成树分割法，检索利用的是小波和共生矩阵提取的特征。-Analysis using the Weka environment for the development of Java-based content-based image segmentation and retrieval procedures, division of segmentation using minimum spanning tree,
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通过VC++编程实现数字图像的边界检索和图像分割-VC++ programming through the digital image retrieval and image segmentation boundaries
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matlab编写的图像检索代码，依据特征，颜色，边界分割等原理-write matlab code for image retrieval, based on features, colors, borders and other principles of segmentation
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Based on the color characteristics of image segmentation matlab image retrieval source-Image segmentation based on matlab source
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基于matlab的颜色特征图像分割的图像检索源程序-Based on the color characteristics of image segmentation matlab image retrieval source
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基于matlab的颜色特征图像分割的图像检索源程序-Based on the color characteristics of image segmentation matlab image retrieval source
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图像检索完整源程序，包括图像相似度计算、特征提取、图像分割等-Image retrieval complete source code, including image similarity calculation, feature extraction, image segmentation
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提出了一种新的基于区域的图像检索方法。与传统的基于区域的检索方法相比，论文从组成目标对象的基本结构角度出发分割图像，利用少量色彩等级更易描述对象主要构成的特性提取一组能够描述对象基本组成的区域序列。采用这些区域列的面积作为图像特征，用于图像检索。-A new region-based image retrieval. Traditional region-based retrieval methods, papers from the composition of the basic struc
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基于内容的图像检索技术的关键在于特征提取，是利用图像的颜色、形状、纹理、轮廓、对象的空间关系等客观独立的存在于图像中的基本视觉特征作为图像的索引，计算查询图像和目标图像的相似距离，按相似度匹配进行检索。综合国内外研究现状，可将基于内容的图像检索技术分为如下几种类型:基于颜色特征的检索、基于纹理特征的检索、基于形状及区域的检索、基于空间约束关系的检索。-Based on comparing various affine invariant regional basis, selection of
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult
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在图像检索时先对图像进行预处理，其中一个预处理的方法就是图像分割。-In the first image when the image retrieval pretreatment, pretreatment method is one of image segmentation.
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Image segmentation is an important processing in many applications such as
image retrieval and computer vision. One of the most successful models for image segmentation is the level set methods which are based on local context. The methods, though c
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