TY - GEN
T1 - Extending page segmentation algorithms for mixed-layout document processing
AU - Winder, Amy
AU - Andersen, Tim
AU - Barney Smith, Elisa H.
PY - 2011
Y1 - 2011
N2 - The goal of this work is to add the capability to segment documents containing text, graphics, and pictures in the open source OCR engine OCRopus. To achieve this goal, OCRopus' RAST algorithm was improved to recognize non-text regions so that mixed content documents could be analyzed in addition to text-only documents. Also, a method for classifying text and non-text regions was developed and implemented for the Voronoi algorithm enabling users to perform OCR on documents processed by this method. Finally, both algorithms were modified to perform at a range of resolutions. Our testing showed an improvement of 15-40% for the RAST algorithm, giving it an average segmentation accuracy of about 80%. The Voronoi algorithm averaged around 70% accuracy on our test data. Depending on the particular layout and idiosyncracies of the documents to be digitized, however, either algorithm could be sufficiently accurate to be utilized.
AB - The goal of this work is to add the capability to segment documents containing text, graphics, and pictures in the open source OCR engine OCRopus. To achieve this goal, OCRopus' RAST algorithm was improved to recognize non-text regions so that mixed content documents could be analyzed in addition to text-only documents. Also, a method for classifying text and non-text regions was developed and implemented for the Voronoi algorithm enabling users to perform OCR on documents processed by this method. Finally, both algorithms were modified to perform at a range of resolutions. Our testing showed an improvement of 15-40% for the RAST algorithm, giving it an average segmentation accuracy of about 80%. The Voronoi algorithm averaged around 70% accuracy on our test data. Depending on the particular layout and idiosyncracies of the documents to be digitized, however, either algorithm could be sufficiently accurate to be utilized.
KW - open source OCR
KW - page segmentation
KW - RAST
KW - Voronoi
UR - http://www.scopus.com/inward/record.url?scp=82355172996&partnerID=8YFLogxK
U2 - 10.1109/ICDAR.2011.251
DO - 10.1109/ICDAR.2011.251
M3 - Conference contribution
AN - SCOPUS:82355172996
SN - 9780769545202
T3 - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SP - 1245
EP - 1249
BT - Proceedings - 11th International Conference on Document Analysis and Recognition, ICDAR 2011
T2 - 11th International Conference on Document Analysis and Recognition, ICDAR 2011
Y2 - 18 September 2011 through 21 September 2011
ER -