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Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 88-288
Full Name: Hsiao-Wei Chang
Position: Lecturer
Age: ON
Sex: Male
Address: 245, Sec. 3, Academia Road, Taipei City 11581, Taiwan
Country: TAIWAN
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E-mail address: changhw@cc.cust.edu.tw
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Title of the Paper: Robust News Video Text Detection Based on Edges and Line-deletion
Authors as they appear in the Paper: Shwu-Huey Yen, Hsiao-Wei Chang, Chia-Jen Wang, Chun-Wei Wang
Email addresses of all the authors: 105390@mail.tku.edu.tw, changhw@cc.cust.edu.tw, chiajen.wang@msa.hinet.net, 895410024@s95.tku.edu.tw
Number of paper pages: 10
Abstract: This paper presents a robust and efficient text detection algorithm for news video. The proposed algorithm uses the temporal information of video and logical AND operation to remove most of irrelevant background. Then a window-based method by counting the black-and-white transitions is applied on the resulted edge map to obtain rough text blobs. Line deletion technique is used twice to refine the text blocks. The proposed algorithm is applicable to multiple languages (English, Japanese and Chinese), robust to text polarities (positive or negative), various character sizes (from 4¡Ñ7 to 30¡Ñ30), and text alignments (horizontal or vertical).Three metrics, recall (R), precision (P), and quality of bounding preciseness (Q), are adopted to measure the efficacy of text detection algorithms. According to the experimental results on various multilingual video sequences, the proposed algorithm has a 96% and above performance in all three metrics. Comparing to existing metho!
ds, our method has better performance especially in the quality of bounding preciseness that is crucial to later binarization process.
Keywords: Information retrieval, Multiple frames integration, Video text, Text detection, Canny edge map, Black-white transition, Line-deletion
EXTENSION of the file: .doc
Special (Invited) Session: Precise News Video Text Detection/Localization Based on Multiple Frames Integration
Organizer of the Session: 647-124
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