Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Text information extraction in images and video
T2 - a survey
AU - Jung, Keechul
AU - Kim, Kwang In
AU - Jain, Anil K.
PY - 2004/5
Y1 - 2004/5
N2 - Text data present in images and video contain useful information for automatic annotation, indexing, and structuring of images. Extraction of this information involves detection, localization, tracking, extraction, enhancement, and recognition of the text from a given image. However, variations of text due to differences in size, style, orientation, and alignment, as well as low image contrast and complex background make the problem of automatic text extraction extremely challenging. While comprehensive surveys of related problems such as face detection, document analysis, and image & video indexing can be found, the problem of text information extraction is not well surveyed. A large number of techniques have been proposed to address this problem, and the purpose of this paper is to classify and review these algorithms, discuss benchmark data and performance evaluation, and to point out promising directions for future research.
AB - Text data present in images and video contain useful information for automatic annotation, indexing, and structuring of images. Extraction of this information involves detection, localization, tracking, extraction, enhancement, and recognition of the text from a given image. However, variations of text due to differences in size, style, orientation, and alignment, as well as low image contrast and complex background make the problem of automatic text extraction extremely challenging. While comprehensive surveys of related problems such as face detection, document analysis, and image & video indexing can be found, the problem of text information extraction is not well surveyed. A large number of techniques have been proposed to address this problem, and the purpose of this paper is to classify and review these algorithms, discuss benchmark data and performance evaluation, and to point out promising directions for future research.
KW - Text information extraction
KW - Text detection
KW - Text localization
KW - Text tracking
KW - Text enhancement
KW - OCR
U2 - 10.1016/j.patcog.2003.10.012
DO - 10.1016/j.patcog.2003.10.012
M3 - Journal article
VL - 37
SP - 977
EP - 997
JO - Pattern Recognition
JF - Pattern Recognition
SN - 0031-3203
IS - 5
ER -