【作者】 刘金梅；

【导师】 王国宇；

【作者基本信息】 中国海洋大学 ， 信号与信息处理， 2004， 硕士

【摘要】 本文提出了一种新的基于内容检索图像的方法——基于块划分颜色特征的图像检索方法。该方法利用栅格划分技术提取图像颜色特征，通过对图像的分块编码，将图像转换成类似文本的形式，并借用成熟的文本模型分析图像特征分布。 由于利用颜色特征能够简化目标的提取和识别，所以在图像检索中，颜色是应用最广泛的视觉属性。传统的表示颜色特征的直方图法只能表示颜色的组成，没有包含颜色的空间分布信息，难以区分颜色组成相似但是空间分布不同的图像。为了克服颜色直方图的缺点，本文提出了一种新的基于颜色及其空间分布的图像检索方法。该方法将图像划分成大小相等的图像块，然后提取每一块的颜色信息作为特征矢量。通过对特征矢量聚类编码，图像内容可以表示为空间分布信息的局部颜色特征组合，进而可以应用基于文本的检索技术实现图像检索。实验证明，用此方法表示图像不但可以实现对无约束场景图像的有效检索，而且能够较好地实现查询和定位区域图像。 在所有基于块分割的图像描述方法中，块大小的选择是一个影响特征表示有效性的重要问题，以往的方法中都依赖于经验选择分割尺度。本文着重对该问题进行了研究，采用信息熵作为衡量划分优劣的标准，在优化的意义下对块划分窗口进行选择。实验证明，这样选择的划分窗口是有意义的，能够提高检索的有效性。更多还原

【Abstract】 This paper provides a new image retrieval approach: Partition-based color image retrieval. Partition is used to extract spatial information and by coding, image can be transformed into a text-image. So images can be analyzed by mature text model.Color is a common used feature in content-based image retrieval for it simplifies object identification. The traditional approach to using the color information of an image is color histogram, which is insensitive to translation and rotation. But its drawback is prone to yield false hits in large database because of lacking spatial information. To solute the problem, we try to combine spatial information with color feature to improve the performance of content-based image retrieval. This is achieved by partitioning images in the training set into fixed size cells and, for each cell, extracting a local color histogram as the color invariant feature of the cell. All of the color invariant features are clustered into a number of patterns. Thus all the images in the database can be regarded as a collection of those patterns. Images are recognized by their patterns, which takes a step to retrieve image by symbolic notions. Thereby the well-developed text retrieval method can be applied for image’query and index through such symbolic descriptions. Experimental results show that the new method is robust in retrieving images with domain-free scenes and is efficient in sub-region retrieval and localization.For all the partition-based image retrieval, choosing a proper partitioning scale is a significant problem and is usually determined subjectively. This paper proposes information entropy as a measure of optimal scale and experimental results show it is reasonable.更多还原