System on Visual Information Retrieval Considering Human Perception for Grouping Areas in Images

为增强考虑人类主体的商标图像CBIR （Content-Based Image Retrieval）系统，实现了以下课题：然后，研究了它们应用于其他图像的CBIR系统的可能性。(1)提出了格式塔心理学中“接近性”、“相似性”、“封闭性”和“良好连续性”的聚类因子模型，设计了一种判别分析识别抽象商标聚类区域的方法。(2)根据抽象性商标形象分组问卷调查结果，设计了分组因子“平行性”模型。(3)为了从体育直播视频中提取元数据，利用直播视频中比分横幅在每一局有规律变化的现象，将一局中的所有火焰视为一组，即通过引入(1)中提出的方法，提出了一种将每一局的火焰分组为一组火焰的方法。(4)设计尘肺病计算机辅助诊断(1)中提出的部分模型应用于CCD扫描仪获得的胸部x线片的降噪。

For the research for enhancing a CBIR (Content-Based Image Retrieval) system of trademark images considering human subjects, the following subjects were realized. And then, the possibility they can be applied to CBIR systems for other images was investigated.(1) Models for the grouping factors of "proximity", "similarity", "closure", and "good continuity" in the Gestalt Psychology were proposed and a method for recognizing grouping areas in abstract trademarks by discrimination analysis was designed.(2) According to results of questionnaire on the image grouping using abstract trademarks, a model of a grouping factor "parallerism" was designed.(3) For the purpose of extracting metadata from sports broadcasted videos, using the phenomenon that the score banner in the broadcasted videos regularly change in every inning, all the flames in a inning are regarded as a group, i.e., a method for grouping flames into sets of flames in every inning was proposed by introducing the method proposed in (1).(4) For designing a computer-aided diagnosis in pneumoconiosis, a part of the models proposed in (1) was applied for noise reductions in chest radiographs obtained from a CCD scanner.