TY - GEN
T1 - Detection and segmentation of antialiased text in screen images
AU - Gleichman, Sivan
AU - Ophir, Boaz
AU - Geva, Amir
AU - Marder, Mattias
AU - Barkan, Ella
AU - Packer, Eli
PY - 2011/12/2
Y1 - 2011/12/2
N2 - Various software applications deal with analyzing the textual content of screen captures. Interpreting these images as text poses several challenges, relative to images traditionally handled by optical character recognition (OCR) engines. One such challenge is caused by text antialiasing, a technique which blurs the edges of characters, to reduce jagged appearance. This blurring changes the character images according to context, and can sometimes fuse them together. In this paper, we offer a low-cost method that can be used as a preprocessing stage, prior to OCR. Our method locates antialiased text in a screen image and segments it into separate character images. Our proposed algorithm significantly improves OCR results, particularly in images with colored text of small font size, such as in graphic user interface (GUI) screens.
AB - Various software applications deal with analyzing the textual content of screen captures. Interpreting these images as text poses several challenges, relative to images traditionally handled by optical character recognition (OCR) engines. One such challenge is caused by text antialiasing, a technique which blurs the edges of characters, to reduce jagged appearance. This blurring changes the character images according to context, and can sometimes fuse them together. In this paper, we offer a low-cost method that can be used as a preprocessing stage, prior to OCR. Our method locates antialiased text in a screen image and segments it into separate character images. Our proposed algorithm significantly improves OCR results, particularly in images with colored text of small font size, such as in graphic user interface (GUI) screens.
KW - antialiasing
KW - character segmentation
KW - text detection
UR - http://www.scopus.com/inward/record.url?scp=82355186463&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/ICDAR.2011.92
DO - https://doi.org/10.1109/ICDAR.2011.92
M3 - Conference contribution
SN - 9780769545202
T3 - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SP - 424
EP - 428
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 -