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形状匹配和基于内容图象检索
丁险峰
学位类型工学博士
导师马颂德
2000-02-01
学位授予单位中国科学院自动化研究所
学位授予地点中国科学院自动化研究所
学位专业模式识别与智能系统
摘要静态图象的检索涉及许多图象特征,包括颜色、纹理、骨架、形状(轮廓)、 空间约束、客观特性、主观特性、领域知识等多个方面。在本文主要研究如何 抽取图象的底层特征,如图象的形状、颜色、纹理。重点研究了形状匹配的几 种方法,包括形状匹配的随机优化方法和解析匹配算法;发展了基于共生矩阵 的纹理分析方法;改进了颜色空间聚类算法和基于区域的图象检索方法。 我们改进了基于点对应进行形状匹配的Hopfield神经网络的能量公式, 修改了网络结构和迭代算法,从而满足了部分遮掩形状匹配问题对神经网络的 要求,使得网络能够收敛到最优的匹配结果,因此可以解决更加剧烈的遮掩问 题。遗传算法是一种先进的优化工具,在某些场合比神经网络能更好的处理优 化问题,我们应用了遗传算法来解决部分遮掩形状匹配问题,获得了很好的结 果.形状可以看成两个一维信号,如果有大量同类形状作为训练样本,那么构 造一个隐Markov模型来刻划形状比变形模板更适合于形状匹配问题。 许瓦兹表示是我们实验室多年来的研究结果[64],本论文通过对许瓦兹积 分的物理意义的分析判明许瓦兹积分实际上与柯西积分有着本质相同的关系。 利用这一特性我们构建了许瓦兹尺度空间;分析了一些它的基本特点。结合了 一些解析函数的优美结果提出了尺度自动选择的方法,提出多尺度Fourier描 绘子的概念,从而提高了形状匹配的速度.另外我们还利用许瓦兹尺度空间来 提取形状的关键点,达到了简化形状的目的。 检索的两个主要关键在于它的高效性和准确性。我们设计了一个三层的层 次化的检索框架。在第一层中,使用形状的几何特征来对整个数据库建索引, 实现了高效性。Fourier描绘子在第二层中用来过滤上一层的输出结果。在第 三层中,我们使用多尺度Fourier描绘子来改进第二层的结果。 为了验证算法的正确性,我们建立了_个图象检索的演示系统,取得了良 好的结果,在不同程度上改进了基于纹理、颜色、区域的图象检索的方法。
其他摘要Image retrieval all feature of image, such as color, texture, sketch, (shape) contour, spatial relation, objective feature, subjective feature, knowledge of domain etc. In this paper, we mainly study how to extract the lower feature of image, i.e. shape, texture, and color. We mainly studied several methods of shape matching, including the stochastic method and analytic method, developed methods based on coconcurrence matrix, improved the color space cluster algorithm and algorithm for region based image retrieval. Hopfield neural network is typical optimization method for shape match, we improved the structure of the network, update algorithm, and the energy function to adapt to the specification of problem of occluded shape matching. Genetic algorithm is an advanced optimization method, in some case, it perform better than neural network. We apply the genetic algorithm to solve problem of the partial occluded shape matching. The result is good. Each shape can be characterized by two one- dimensional signals. So if there exist a lot of shapes in same class, you can use them as train material and build a HMM to characterize shape. Schwarz representation had been studied in our lab for several years. In this paper we show that Schwarz integrals is same as Cauchy integral after studying the physical meaning of it. Based on this property, we build the Schwarz scale space and proposed some property of it. With the elegant result analytic function, the automatic scale selection algorithm is developed. Multi-scale Fourier descriptor is proposed to accelerate the speed of shape matching. We also utilize the Schwarz scale space to extract the dominant point of shape to achieve the simplification of shape. The key problem of image retrieval is effectiveness and efficiency. We designed a three layer hierarchical framework for shape based image retrieval. In the first layer we build the index for shape by their geometric feature. In the second layer Fourier descriptor is used to filter sub-database. In the third layer, we use multi-scale Fourierdescriptor to improve the result of second layer. In order to verify those algorithm, we built a demo system of image retrieval, on the platform the color, texture, region based image retrieval technique is implemented. The result is very good.
馆藏号XWLW547
其他标识符547
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/5707
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
丁险峰. 形状匹配和基于内容图象检索[D]. 中国科学院自动化研究所. 中国科学院自动化研究所,2000.
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