A Study on Fast Search Algorithm in Large Scale Image Database based on Correlation Analysis

基于相关分析的大规模图像数据库快速检索算法研究

• 批准号: 14580401
• 负责人: KANEKO Shun'ichi
• 金额: $ 2.05万
• 依托单位: HOKKAIDO UNIVERSITY
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2002
• 资助国家: 日本
• 起止时间: 2002 至 2003
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-14580401/
• 关键词: Image retrieval; Correlation; Fast algorithm; Image Database; Correlation analysis; Pivot image; 画像データペース; 正規化相関

A rapid algorithm of searching for similar images to an object image in a set of registered images is proposed. The set of images is assumed to be processed to have correlation coefficients for all the pairs of registered images in advance and in offline. For designing the algorithm, by an indirect way through any pivot image, we mathematically derive a constraint inequality about correlation coefficients between any registered images and the object image provided. The inequality shows a range of values of estimated correlation coefficients for unknown registered images. Mainly by use of the upper bounds defined by the inequality, three conditions for selecting redundant or neglected images having small similarity from the total image set can be derived, which enable to quicken computation of searching. The rapid algorithm is applied to real world searching problems with the set of 1,200 images of Japanese characters, Hirakana. Efficiency rate of eight times in average could be obtained for searching 204 object images of various similarities, enabling to show the effectiveness of the proposed method for real world tasks of image retrieval in large scale image database systems, media database, and data mining systems. The proposed algorithm can be applied for decreasing computational cost in cooperation with some existing schemes, such as SSDA, and random sampling.

提出了一种在配准图像集中快速搜索与目标图像相似图像的算法。假设预先和离线地处理图像集合以具有所有登记图像对的相关系数。为了设计该算法，通过一个间接的方式通过任何枢轴图像，我们在数学上推导出一个约束不等式的相关系数之间的任何注册的图像和目标图像提供。不等式示出了用于未知注册图像的估计相关系数的值的范围。主要是利用不等式定义的上界，导出了从总图像集中选择相似性小的冗余或忽略图像的三个条件，从而加快了搜索的计算速度。该快速算法被应用于真实的世界的搜索问题与一组1,200图像的日本字符，平假名。对204幅不同相似度的目标图像进行检索，平均检索效率可达8倍，表明该方法在大规模图像数据库系统、媒体数据库和数据挖掘系统等真实的图像检索任务中的有效性。该算法可与SSDA、随机抽样等现有算法配合使用，以降低计算量。

项目成果

Shun'ichi KANEKO: "Robust Sensing via Image Information"Journal of JSPE. vol.69, no.10. 1383-1386 (2003)

Shunichi KANEKO：“通过图像信息进行鲁棒传感”JSPE 杂志。

Takahiro MAE: "Efficient Image Search by Estimating Correlation through Constraint Inequality"Proc.of Japan-France Congress on Mechatonics. 303-308 (2003)

Takahiro MAE：“通过约束不等式估计相关性进行高效图像搜索”日法机电学大会论文集。

金平祐介: "弛緩テンプレート照合による海表面速度場の推定"電子情報通信学会論文誌. J86. 846-855 (2003)

Yusuke Kanehira：“通过松弛模板匹配估计海面速度场”，电子、信息和通信工程师学会学报 J86-855（2003 年）。

Hiroshi SHIMONO: "Fast Rotated Image Matching based on Two-dimensional Orthogonal Expansion by Marginal Eigenvectors"Journal of JSPE. vol.68, no.8. 1402-1046 (2003)

Hiroshi SHIMONO：“基于边缘特征向量二维正交扩展的快速旋转图像匹配”JSPE 期刊。

田中理恵, 金子俊一: "統計的不在確認による高速画像探索"画像電子学会誌. 32・4. 369-377 (2003)

Rie Tanaka、Shunichi Kaneko：“使用统计缺席确认的高速图像搜索”日本图像电子工程师学会杂志 32・4（2003 年）。