Support vector machines for text location in news video images
Support vector machines for text location in news video images
复制标题
用于新闻视频图像中文本定位的支持向量机
DOI：
10.1109/tencon.2000.888824
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发表时间：
2000
期刊：
影响因子：
--
通讯作者：
Se Hyun Park
中科院分区：
文献类型：
--
作者：
K. Jung;J. Han;K. Kim;Se Hyun Park
本文的目的是展示支持向量机（SVMs）对于文本定位问题的适用性，并提出一种基于支持向量机的新闻视频图像文本定位方法。所提出的方法是基于观察数字视频中的文本具有不同的纹理属性，可以用来区分文本的背景和SVM可以被训练成一个纹理分类器。支持向量机通过分析视频图像的纹理特征，将像素分为文本和非文本。为了实现多尺度定位，视频图像被递增地调整大小，并且在这些调整大小的图像中的每一个上执行定位过程。
The aim of this paper is to show the applicability of support vector machines (SVMs) for the problem of text location and to propose an SVM-based method for locating texts in news video images. The proposed method is based on observations that texts in digital video have distinct textural properties that can be used to discriminate texts from the background and an SVM can be trained to be a texture classifier. An SVM is used for classifying a pixel into text or non-text by analyzing the textural properties of video image. To achieve multi-scale location, the video image is incrementally resized and the location process is performed over each of these resized images.