图像数据挖掘的模型和技术  

Frameworks and techniques of image mining

作　　者：薄华[1] 马缚龙[1] 焦李成[1] 

机构地区：[1]西安电子科技大学自动化系,陕西西安710071

出　　处：《西安邮电学院学报》2004年第3期81-85,共5页Journal of Xi'an Institute of Posts and Telecommunications

摘　　要：图像获取和存储技术的进步使人们每天都可以获取大量的包含很多对有用的信息图像数据,但缺乏有效的工具分析这些数据。图像数据挖掘的任务就是分析、提取海量图像中隐含的有用的信息和模式,发现图像数据间的关系。图像数据挖掘并不只是数据挖掘在图像领域的简单应用,它是一门包括计算机视觉,图像处理,图像检索,数据挖掘,机器学习,数据库和人工智能等的综合学科。本文将介绍现有的图像数据挖掘的模型和技术。Advances in image acquisition and storage technology have led to tremendous growth in significantly large and detailed image databases. These images reveal large and useful information to human users. But the problem is there are no useful tools to found them. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. We will describe the frameworks and techniques of image mining in this paper.

关 键 词：图像挖掘 图像检索 机器学习 人工智能 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]