A Picture Retrieval System Based on Contents

这是一个由伊利诺伊大学芝加哥分校（UIC）和赖特州立大学（WSU）参与的机构间合作研究项目。基于内容检索图像的图像系统有着广泛的应用。例如，可以通过从电子百科全书中检索图片来促进学习；放射科医生可以协助诊断；地球科学家可以检索所需内容的卫星图像进行研究；顾客可以先看看合适的服装，然后再决定去哪里购物等等。该项目的目的是构建一个通用的图像检索和分析系统，该系统可以很容易地适应各种应用，包括数字图书馆的建设和它们在信息检索中的使用。基于相似度的检索涉及空间关系，模糊匹配和精确匹配是研究的方法之一。其他发挥重要作用的技术有：多维搜索；参数化相似函数；可视化查询工具；图像分割等分析技术；目标识别;以及颜色和形状分析。检索子系统是在UIC开发的，图像分析子系统是在WSU开发的。这两个子系统将结合起来形成一个综合系统。该系统的有用性将在下列应用中得到证明：为芝加哥大学的照相室检索照片，以及为芝加哥拉什-长老会医疗中心的皮肤癌诊断检索图像。

This is an inter-institutional collaborative research project involving University of Illinois at Chicago (UIC) and Wright State University (WSU). Pictorial systems which retrieve pictures based on contents have wide applications. For example, learning can be facilitated by retrieving pictures from electronic encyclopedia; radiologists can be assi sted in diagnosis; satellite images of desired contents can be retrieved by earth scientists to perform research; appropriate garments can be viewed by customers before deciding where they go shopping, etc. The purpose of the project is to construct a generic picture retrieval and analysis system which can be easily adapted to various applications , including the construction of digital libraries and their use in retrieval of information. Similarity based retrieval involving spatial relationships, and fuzzy and precise matching is used one of the approaches investigated. Other techniques that play a significant role are: multi-dimensional searching; parametrized similarity functions; visual query tools; image analysis techniques such as segmentation; object recognition; and color and shape analysis. The retrieval subsystem is developed at UIC, while the image analysis subsystem is developed at WSU. The two subsystems will be combined to form an integrated system. The usefulness of the system will be demonstrated for the following ap plications: retrieval of photographs for the photo-shop at UIC, and retrieval of images for diagnosis of skin cancer at Rush-Presbyterian Medical Center in Chicago.