Graphics recognition for a large-scale airplane information system

Abstract

The Boeing Company maintains tens of millions of pages of information associated with the manufacture and delivery of its products. Much of this information must be made available electronically. We have developed tools to automatically convert and integrate electronic data into industry standard formats. Some of the technical challenges include 1) handling a wide variety of source formats, 2) making sure that the tools scale up to handle millions of pages of information, and 3) adding functionality to graphics. Our system contains over four million pages of text including tens of thousands of graphics.

In this paper we describe tools that recognize and use information within airplane-related vector and raster images. Such images include troubleshooting charts, fault reporting diagrams, component location diagrams, component index tables, wiring diagrams, system schematics, parts illustrations, standards tables, and structural and tooling drawings. Each airplane requires conversion of over 20,000 graphics, including over 900,000 pieces of cross-referenced information. We are also exploring visual information retrieval strategies, including content-based and similarity-based methods for both vector and raster graphics.