Visual Text Features for Image Matching

Sam S. Tsai, Huizhong Chen, David M. Chen, Vasu Parameswaran, R. Grzeszczuk, B. Girod
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引用次数: 7

Abstract

We present a new class of visual text features that are based on text in camera phone images. A robust text detection algorithm locates individual text lines and feeds them to a recognition engine. From the recognized characters, we generate the visual text features in a way that resembles image features. We calculate their location, scale, orientation, and a descriptor that describes the character and word information. We apply visual text features to image matching. To disambiguate false matches, we developed a word-distance matching method. Our experiments with image that contain text show that the new visual text feature based image matching pipeline performs on par or better than a conventional image feature based pipeline while requiring less than 10 bits per feature. This is 4.5× smaller than state-of-the-art visual feature descriptors.
图像匹配的视觉文本特征
我们提出了一种新的基于相机手机图像文本的视觉文本特征。鲁棒文本检测算法定位单个文本行并将其提供给识别引擎。从识别的字符中,我们以类似于图像特征的方式生成视觉文本特征。我们计算它们的位置、比例、方向以及描述字符和单词信息的描述符。我们将视觉文本特征应用于图像匹配。为了消除错误匹配的歧义,我们开发了一种词距匹配方法。我们对包含文本的图像进行的实验表明,新的基于视觉文本特征的图像匹配管道的性能与传统的基于图像特征的管道相当或更好,而每个特征所需的数据少于10位。这比最先进的视觉特征描述符小4.5倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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