The Design of Images Database by Using Bootstrapping

• Main Authors: Yi-Fan Chen, 陳一帆
• Other Authors: Chin-Hwa Kuo
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/05339863911065750889

碩士 === 淡江大學 === 資訊工程學系碩士班 === 94 === In this paper, we have designed a database that can automatically classify images, for the purpose of sorting through a large number of images more conveniently and thus save manpower and resources. This database is characterized by high level features (text-based) to image classifying. Its features include: extending a keyword through bootstrapping construction. First of all bootstrapping construction method extended words that the user manually inputted, and then increased the value and number of classificatory keywords. The keywords and classificatory keywords after extension underwent similarity value calculations. Finishing this step results in an initial classifying for images, and the step is repeated until there are no more changes in the classifications. Whereas common ways of extending a keyword deal with its definition, bootstrapping construction allows expansion through associative extension. This type of keyword expansion mechanism is capable of classifying images in ways that WordNet cannot. Aside from using bootstrapping construction to expand keywords and to classify images, we have also added a discriminative feature metric to increase the precision and recall rates of image classifying to our standards.