With the advent of on-line access to very large collections of document images, electronic classification into areas of interest has become possible. A first approach to classification might be the use of OCR on each document followed by analysis of the resulting ASCII text. But if the quality of a document is poor, the format unconstrained, or time is critical, complete OCR of each image is not appropriate. An alternative approach is the use of word shape recognition (as opposed to individual character recognition) and the subsequent classification of documents by the presence or absence of selected keywords. Use of word shape recognition not only provides a more robust collection of features but also eliminates the need for character segmentation (a leading cause of error in OCR). In this paper we describe a system we have developed for the detection of isolated words, word portions, as well as multi-word phrases in images of documents. It is designed to be used with large, changeable, keyword sets and very large document sets. The system provides for automated training of desired keywords and creation of indexing filters to speed matching.