By HS Baird and Ken Thompson.
“In an application of semantic analysis to images of extended passages of text, several volumes of a chess encyclopedia have been read with high accuracy. Although carefully proofread, the hooks were poorly printed and posed a severe challenge to conventional page layout analysis and character-recognition methods. An experimental page reader system carried out strictly top-down layout analysis for identification of columns, lines, words, and characters. This proceeded rapidly and reliably thanks to a recently-developed skew-estimation technique. Resegmentation of broken, touching, and dirty characters was handled in an efficient and integrated manner by a heuristic search operating on isolated words. By analyzing the syntax of game descriptions and applying the rules of chess, the error rate was reduced by a factor of 30 from what was achievable through shape analysis alone. Of the games with no typographical errors, 98% have been assigned a legal interpretation, for an effective success rate of 99.995% on approximately one million characters (2850 games, 945 pages). We discuss several computer vision systems-integration issues suggested by this experience.”
Keywords: Character recognition, chess, document image analysis, layout analysis, semantics.
- reading_chess.pdf (PDF)