TY - JOUR
T1 - 3D rotation angle estimation of camera captured characters
AU - Kuramoto, Kanta
AU - Ohyama, Wataru
AU - Wakabayashi, Tetsushi
AU - Kimura, Fumitaka
N1 - Publisher Copyright:
© 2014 The Institute of Electrical Engineers of Japan.
PY - 2014
Y1 - 2014
N2 - Recently, expectations for camera-based document analysis and recognition have increased by improved performance of digital camera devices. In this paper, we propose a rotation angle estimation method using Gray-Scale Gradient Feature and Modified Quadratic Discriminant Function (MQDF). This method can recognize characters and estimate the rotation angle of those characters rapidly. As the result of the evaluation experiment using printed alphanumeric character, we have confirmed that the low dimensional feature vector is sufficient to estimate the rotation angle of characters. Also, we reduced the number of used eigenvectors of the covariance matrix to calculate the MQDF while keeping estimation accuracy.
AB - Recently, expectations for camera-based document analysis and recognition have increased by improved performance of digital camera devices. In this paper, we propose a rotation angle estimation method using Gray-Scale Gradient Feature and Modified Quadratic Discriminant Function (MQDF). This method can recognize characters and estimate the rotation angle of those characters rapidly. As the result of the evaluation experiment using printed alphanumeric character, we have confirmed that the low dimensional feature vector is sufficient to estimate the rotation angle of characters. Also, we reduced the number of used eigenvectors of the covariance matrix to calculate the MQDF while keeping estimation accuracy.
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U2 - 10.1541/ieejeiss.134.1817
DO - 10.1541/ieejeiss.134.1817
M3 - Article
AN - SCOPUS:84916604264
VL - 134
SP - 1817
EP - 1823
JO - IEEJ Transactions on Electronics, Information and Systems
JF - IEEJ Transactions on Electronics, Information and Systems
SN - 0385-4221
IS - 12
ER -