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基于模糊熵的空间语义图像检索模型研究* 总被引:1,自引:0,他引:1
根据模糊熵理论和改进的空间信息分布,提出了颜色空间特征语义图像检索模型。阐述基于语法规则的颜色空间特征语义描述方法,构造从低层颜色空间特征到高层语义之间的映射,根据这些模糊语义值进行图像检索。实验结果表明,该模型能够有效地对图像高层语义进行刻画,由此实现的模型不仅能获得高效和稳定的检索结果,获得与人类视觉感知较好的一致性,该算法还能很好地消除低层图像空间特征和高层语义之间的语义鸿沟。 相似文献
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为了弥补图像低层视觉特征和高层语义之间的"语义鸿沟",改善图像自动标注的性能,提出了基于多媒体描述接口(MPEG-7)和MM(Mixture Model)混合模型的图像标注算法。该算法采用MPEG-7标准推荐的颜色和纹理描述子提取图像的低层视觉特征,通过MM混合模型建立低层特征到高层语义空间的映射,实现了基于图像整体低层特征的多标签图像自动标注。通过在corel图像数据集上的一系列实验测试验证了该方法的可行性和有效性。 相似文献
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为了缩短介于低层视觉特征与高层语义特征之间的“语义鸿沟”距离,提出了急需解决的两大关键问题。首先按语义抽象程度给出了一种图像语义层次模型,着重分析与比较了四种语义信息提取方法的特点和存在问题;然后介绍了几种典型的语义特征相似性度量方法,阐述了目前图像理解应用的研究现状;最后搭建了图像语义理解框架,讨论了智能图像语义理解的未来研究趋势。 相似文献
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在CBIR研究中,图像低层视觉特征和高层语义特征之间存在的“语义鸿沟”成为语义图像检索的关键问题。为了避免一般映射方法把一幅图像归于一类语义图像的现象,体现自然风景图像中包含的丰富的高层语义信息和多归属类型,提出了对自然风景彩色图像中颜色较单一的目标区域,重复采用最优阈值化进行一次粗分割来提取最大目标区域,在分割区域的基础上,提取图像的局部颜色和形状特征,最后利用改进的模糊神经网络来建立低层视觉特征和高层语义特征之间的映射,实现了图像属性信息的有效传递和高层语义的自动获取。实验结果表明,该图像分割方法对自然彩色图像能够有效地提取目标物体,并对噪声图像具有一定的鲁棒性,而语义图像的部分类别的检索准确率接近90%,查全率也达到了75%,实验结果证明了该方法对自然图像检索的有效性及先进性。 相似文献
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针对图像的低层视觉特征和高层语义特征之间的鸿沟,利用一个多输出的BP神经网络,分析低层视觉特征,提取图像的主要颜色、灰度共生矩阵和7个不变矩向量作为网络的输入,用语义期望值作为网络的输出,并用加入动量因子和自适应学习率的BP算法来训练该网络。训练完成后,该网络能够对自然图像进行多种语义分类,从而建立起了从低层视觉特征到语义特征之间的映射。改进的BP算法提高了训练的速度和可靠性,实验证明,该方法取得了较好的检索查全率和准确率。 相似文献
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《Displays》2023
3D reconstruction technique based on deep learning is gaining increasing attention from researchers. The majority of current 3D reconstruction techniques require a simple background, which limit their applications on complex background image. Extracting point cloud features comprehensively is also extremely difficult. This paper design a novel 3D reconstruction network to overcome these limitations. Firstly, we get the image and the retrieved point cloud that is the most similar to the input image. Secondly, to learn the features of the retrieved point cloud, the network encodes and decodes the single image and the retrieved point cloud to generate sparse point cloud. Finally, the proposed dense module densifies the sparse point cloud into the dense point cloud. We use single image of complex background and public dataset to evaluate our network. The reconstruction results indicate that the network surpasses previous reconstruction networks. 相似文献
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为了消除服装图像背景的影响,针对目前的GrabCut算法存在对图像局部像素值的变化敏感、时间开销大、边缘不准确等问题,提出了改进的GrabCut算法。在改进算法中,通过对梯度图像使用多尺度分水岭去噪增强了图像的边缘信息,减少了后续处理的计算量;通过采取熵惩罚因子最优能量函数减少了检索图像的有效信息丢失。将改进后的GrabCut算法引入基于内容的服装图像检索系统中,实验结果表明与同类方法相比,所提方法在检索显示准确性以及检索的平均查准率和查全率方面均有明显的提升。 相似文献
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We propose to use adaptive wavelet lifting for image retrieval systems that are based on shape detection and multiresolution structures of objects in a database against a background of texture. To measure the performance of our approach, feature vectors are computed based on moment invariants of detail coefficients produced by the adaptive lifting scheme and retrieval rates are obtained by measuring distances between these vectors. Retrieval rates are compared with the rates obtained when using non-adaptive wavelet filtering as a preprocessing step. A synthetic database is created for this simulation. 相似文献
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一种基于边缘综合特征的彩色图像检索算法 总被引:8,自引:1,他引:7
图像边缘是重要的视觉感知信息,也是图像最基本的特征之一,其在图像分析和理解中有重要价值。以视觉重要的图像边缘轮廓为基础,提出了一种基于边缘综合特征的彩色图像检索新算法。该算法首先利用Canny检测算子提取出原始图像的彩色边缘轮廓;然后构造出能全面反映边缘轮廓内容的两种直方图(边缘颜色直方图和边缘方向直方图);最后综合利用上述两种边缘直方图计算图像间的内容相似度,并进行彩色图像检索。仿真实验表明,该算法能够准确和高效地查找出用户所需内容的彩色图像,并且具有较好的查准率和查全率。 相似文献
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李永芳 《计算机应用与软件》2011,(10)
基于内容的图像检索的关键就是准确地提取图像特征。目前常见的图像特征的分类有颜色、纹理和形状。提出了改进的图像相关图算法以及纹理矩算法,并采取有效的方法来结合这两种算法实现高效的图像检索,图像相关图不仅反映了图像的灰度统计信息,而且还反映了图像的空间特征和灰度的渐变度。纹理矩是通过计算图像局部区域的力矩来反映图像的纹理特征。二者相结合整合了图像颜色和纹理信息。实验证明,改进的图像相关图以及纹理矩算法优于传统算法,二者通过在有限的空间维度下的结合在很大程度上提高了检索精度。 相似文献
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本文在直方图技术的基础上引入了颜色对方法,将图象的空间特性反映出来,因而能检索具有清晰边界的图象,并且图象的大小变化和旋转以及轻微的光照变化不影响检索结果。 相似文献
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In this work, we are interested in technologies that will allow users to actively browse and navigate large image databases and to retrieve images through interactive fast browsing and navigation. The development of a browsing/navigation-based image retrieval system has at least two challenges. The first is that the system's graphical user interface (GUI) should intuitively reflect the distribution of the images in the database in order to provide the users with a mental picture of the database content and a sense of orientation during the course of browsing/navigation. The second is that it has to be fast and responsive, and be able to respond to users actions at an interactive speed in order to engage the users. We have developed a method that attempts to address these challenges of a browsing/navigation based image retrieval systems. The unique feature of the method is that we take an integrated approach to the design of the browsing/navigation GUI and the indexing and organization of the images in the database. The GUI is tightly coupled with the algorithms that run in the background. The visual cues of the GUI are logically linked with various parts of the repository (image clusters of various particular visual themes) thus providing intuitive correspondences between the GUI and the database contents. In the backend, the images are organized into a binary tree data structure using a sequential maximal information coding algorithm and each image is indexed by an n-bit binary index thus making response to users’ action very fast. We present experimental results to demonstrate the usefulness of our method both as a pre-filtering tool and for developing browsing/navigation systems for fast image retrieval from large image databases. 相似文献