TY - GEN
T1 - An automatic video text detection, localization and extraction approach
AU - Zhu, Chengjun
AU - Yuanxin, Ouyang
AU - Gao, Lei
AU - Chen, Zhenyong
AU - Zhang, Xiong
PY - 2009
Y1 - 2009
N2 - Text in video is a very compact and accurate clue for video indexing= and summarization. This paper presents an algorithm regarding word group as a special symbol to detect, localize and extract video text using support vector machine (SVM) automatically. First, four sobel operators are applied to get the EM(edge map) of the video frame and the EM is segmented into N×2N size blocks. Then character features and characters group structure features are extracted to construct a 19-dimension feature vector. We use a pre-trained SVM to partition each block into two classes: text and non-text blocks. Secondly a dilatation- shrink process is employed to adjust the text position. Finally text regions are enhanced by multiple frame information. After binarization of enhanced text region, the text region with clean background is recognized by OCR software. Experimental results show that the proposed method can detect, localize, and extract video texts with high accuracy.
AB - Text in video is a very compact and accurate clue for video indexing= and summarization. This paper presents an algorithm regarding word group as a special symbol to detect, localize and extract video text using support vector machine (SVM) automatically. First, four sobel operators are applied to get the EM(edge map) of the video frame and the EM is segmented into N×2N size blocks. Then character features and characters group structure features are extracted to construct a 19-dimension feature vector. We use a pre-trained SVM to partition each block into two classes: text and non-text blocks. Secondly a dilatation- shrink process is employed to adjust the text position. Finally text regions are enhanced by multiple frame information. After binarization of enhanced text region, the text region with clean background is recognized by OCR software. Experimental results show that the proposed method can detect, localize, and extract video texts with high accuracy.
KW - Multilingual texts
KW - Support vector machine(SVM)
KW - Video OCR
KW - Video text detection
UR - https://www.scopus.com/pages/publications/67650296360
U2 - 10.1007/978-3-642-01350-8_1
DO - 10.1007/978-3-642-01350-8_1
M3 - 会议稿件
AN - SCOPUS:67650296360
SN - 364201349X
SN - 9783642013492
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1
EP - 9
BT - Advanced Internet Based Systems and Applications - Second International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2006, Revised Selected Papers
T2 - 2nd International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2006
Y2 - 17 December 2006 through 21 December 2006
ER -