| 引用本文: | 郭强,邹广天,连菲,张斯.应用Web标注技术的建筑图像语义采集方法[J].哈尔滨工业大学学报,2017,49(10):158.DOI:10.11918/j.issn.0367-6234.201601001 |
| GUO Qiang,ZOU Guangtian,LIAN Fei,ZHANG Si.A semantic acquisition method of architectural images based on Web annotation technology[J].Journal of Harbin Institute of Technology,2017,49(10):158.DOI:10.11918/j.issn.0367-6234.201601001 |
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| 应用Web标注技术的建筑图像语义采集方法 |
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郭强1,2,3,邹广天1,2,3,连菲1,2,3,张斯1,2,3
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(1.哈尔滨工业大学 建筑学院,哈尔滨150006;2.哈尔滨工业大学 建筑计划与设计研究所,哈尔滨 150006; 3.黑龙江省寒地建筑科学重点实验室(哈尔滨工业大学), 哈尔滨 150006)
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| 摘要: |
| 为解决建筑师难以快速地从互联网中检索到符合创作需求的建筑图像的问题, 提出了应用Web标注技术的建筑图像语义采集方法.首先, 从建筑学角度界定了建筑图像及建筑图像语义的概念和类型; 其次, 给出了该方法的总体框架和操作流程; 最后, 以著名建筑网站为例进行案例演示, 验证了该方法的可行性和有效性.操作流程细分为3个步骤, 以人工添加和在线学习的方式建立建筑语义词典; 运用数据采集软件, 从建筑图像所在网页中分别采集图像名称、图像注释、图像周围文本、所在网页标题、所在网页正文、图像超链接网页标题6项图像相关文本; 根据图像语义提取规则, 从上述文本中提取建筑图像语义, 与图像文件建立关联后存储到建筑图像数据库.案例检验结果表明，该方法是可行的, 具有较强的操作性, 能够自动、批量地从互联网中下载建筑图像, 并采集图像名称、图像类别、图像主题、项目名称、项目类型等30多项特征，有效地克服了建筑图像查询效率较低的问题, 进而提升了建筑师运用互联网图像进行创作的能力.
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| 关键词: Web标注技术 建筑图像 建筑图像语义 建筑语义词典 图像语义采集 |
| DOI：10.11918/j.issn.0367-6234.201601001 |
| 分类号:TU18 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(51178132) |
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| A semantic acquisition method of architectural images based on Web annotation technology |
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GUO Qiang1,2,3,ZOU Guangtian1,2,3,LIAN Fei1,2,3,ZHANG Si1,2,3
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(1.School of Architecture, Harbin Institute of Technology, Harbin 150006, China; 2.Architectural Planning and Design Institute, Harbin Institute of Technology, Harbin 150006, China;3.Heilongjiang Cold Region Architectural Science Key Laboratory (Harbin Institute of Technology), Harbin 150006, China)
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| Abstract: |
| To solve the problem that architects were always having problems in finding suitable architectural images effectively from websites, a semantic acquisition method of architectural images based on web annotation technology was proposed. First, the concepts and types of architectural images and semantics were defined. Second, the framework and operational processes of this method were illustrated. Finally, the feasibility and validity of this method were verified by famous building websites as examples. Regarding to operational process, there were three steps: building the architectural semantic dictionary by adding artificially and learning online; collecting 6 items of image-related texts (image's name, image's annotation, information around images, webpage's title, webpage's body, and the title of image's hyperlink) from websites where the images were founded; collecting semantics of images according to certain rules, relating them to image files and keeping them to the database of architectural images. This study indicates that the proposed method is feasible and easy to be operated. Architectural images can be automatically downloaded in batches and more than 30 items of architectural semantic characteristics will be collected, such as names, categories, themes of architectural images, as well as names and types of projects. As a result, the semantic acquisition method of architectural images will effectively overcome the problem that architectural images are hard to be searched and it will help architects to improve their abilities of innovation by using images from websites.
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| Key words: Web annotation technology architectural images architectural images’ semantics the architectural semantic dictionary images’ semantics acquisition |
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