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Mathematical Morphology and Region Clustering Based Text Information Extraction from Malayalam News Videos

机译:MALAYALAM新闻视频的数学形态学与地区集群的文本信息提取

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Innovations in technologies like improved internet data transfer, advanced digital data compression algorithms, enhancements in web technology, etc. enabled the exponential growth in digital multimedia data. Among the massive multimedia data, news videos are of higher priority due to its rich up-to-date information and historical evidences. This data is rapidly growing in an unpredictable fashion which requires an efficient and powerful method to index and retrieve such massive data. Even though manual indexing is the most effective, it is the slowest and most expensive. Hence automatic video indexing is considered as an important research problem to be addressed uniquely. In this work, we propose a Mathematical Morphology and Region Clustering based Text Information Extraction (TIE) from Malayalam news videos for Content Based Video Indexing and Retrieval (CBVIR). Morphological gradient acts as an edge detector, by enhancing the intensity variations for detecting the text regions. Further an agglomerative clustering is performed to select the significant text regions. The precision, recall and F_1-measure obtained for the proposed approach are 87.45%, 94.85% and 0.91 respectively.
机译:技术的创新,如改进的互联网数据传输,高级数字数据压缩算法,Web技术的增强等。在数字多媒体数据中使指数增长使得。在大规模的多媒体数据中,由于其丰富的最新信息和历史证据,新闻视频具有更高的优先级。这种数据以不可预测的方式迅速增长,这需要一种有效和强大的方法来索引和检索此类大规模数据。尽管手动索引是最有效的,但它是最慢,最昂贵的。因此,自动视频索引被认为是唯一解决的重要研究问题。在这项工作中,我们提出了一种基于Malayalam新闻视频的数学形态和区域聚类,用于基于Malayalam新闻视频,用于基于内容的视频索引和检索(CBVIR)。通过增强用于检测文本区域的强度变化,形态梯度用作边缘检测器。此外,进行附聚类以选择重要的文本区域。为所提出的方法获得的精确度,召回和F_1度量分别为87.45%,94.85%和0.91。

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