项目名称: 基于改进型视觉注意模型的多模态极相似图像检索方法研究
项目编号: No.61501034
项目类型: 青年科学基金项目
立项/批准年度: 2016
项目学科: 无线电电子学、电信技术
项目作者: 罗霄
作者单位: 北京理工大学
项目金额: 23万元
中文摘要: 多模态极相似图像的检索过程中存在如下问题:不同模态图像间与同一模态不同位置图像间都存在差异,现有图像检索算法不能很好的分辨差异来源,导致图像相似度度量标准失效。为解决上述问题,申请人提出了基于改进型视觉注意模型的多模态极相似图像检索算法,其步骤如下:1.分析人眼在比较可见光二维图像与计算机高精度三维建模投影图像时的关注区域变换过程,建立改进型的视觉注意模型;2.提取对图像采集位置变化敏感而对图像模态变化具有鲁棒性的关键参数集群,构建关注区域变化过程中的相似度衡量标准体系;3.将信号分类、信息融合的理念引入图像相似性度量,在保证检索速度的同时进一步提高图像底层特征信息在图像比对的不同阶段的相似性衡量标准精度;4.将该图像检索算法用于解决不同来源的二维图像在三维模型上的精细寻址问题,通过开展观测点运动过程中的目标区域精确跟踪及定位实验验证算法的精度和有效性。
中文关键词: 图像检索;特征匹配;多模影像特征分析;多模影像相似度测度;配准测度
英文摘要: In order to solve the problems in the multi-mode extremely similar image retrieval : the computer can not distinguish whether the difference comes from the different modal or just comes from the image content, which leads to the failure of similarity measure, this project proposes a multi-mode extremely similar image retrieval methods based on improved visual attention model. The main steps of this algorithm as follow: 1. Analyse the changing process of human eyes' visual attention model when they observing the visible light 2D image and 3D computer modeling projected images, and then build a new improved visual attention model just follow this changing process. 2. Extra the ey parameter group which sentitives to image acquisition position modification but robustness to image mode changing, and then build a similarity measure which focus on the visual attention area changing. 3. Take signal classification and information fusion into image similarity measure, improve the similarity meausre precision of image feature information during the different stages but not let the retrieval speed down. 4. Apply this image retrieval method in solving the problem such as addressing the multi-mode 2D image on the 3D model. At the end, verify the feasibility and accuracy of the multi-mode extremely similar image retrieval methods by using the target region accurate tracking and positioning experiment while the observation point is moving.
英文关键词: Image Retrieval;Feature Matching;Analysis of the Multi-mode Image Characteristics;Multi-mode Image Similarity Measure;Registration Measure