The Indexing and Retrieval of Document Images: A Survey

Abstract

The economic feasibility of maintaining large data bases of document images has created a tremendous demand for robust ways to access and manipulate the information these images contain. In an attempt to move toward a paperless office, large quantities of printed documents are often scanned and archived as images, without adequate index information. One way to provide traditional data-base indexing and retrieval capabilities is to fully convert the document to an electronic representation which can be indexed automatically. Unfortunately, there are many factors which prohibit complete conversion including high cost, low document quality, and the fact that many nontext components cannot be adequately represented in a converted form. In such cases, it can be advantageous to maintain a copy of and use the document in image form. In this paper, we provide a survey of methods developed by researchers to access and manipulate document images without the need for complete and accurate conversion. We briefly discuss traditional text indexing techniques on imperfect data and the retrieval of partially converted documents. This is followed by a more comprehensive review of techniques for the direct characterization, manipulation, and retrieval, of images of documents containing text, graphics, and scene images.