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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/59964


    Title: Robust News Video Text Detection Based on Edges and Line-deletion
    Authors: Yen, Shwu-Huey;Chang, Hsiao-Wei;Wang, Chia-Jen;Wang, Chun-Wei
    Contributors: 淡江大學資訊工程學系
    Keywords: Information retrieval;Multiple frames integration;Video text;Text detection;Canny edge map;Black-white transition;Line-deletion
    Date: 2010-10
    Issue Date: 2011-10-05 22:30:56 (UTC+8)
    Publisher: Zographou: World Scientific and Engineering Academy and Society (W S E A S)
    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 4×7 to 30×30), 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 methods, our method has better performance especially in the quality of bounding preciseness that is crucial to later binarization process.
    Relation: WSEAS Transactions On Signal Processing 6(1), pp.186-195
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

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