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A Novel System for Robust Text Location and Recognition of Book Covers

机译:一种新颖的文本封面和书皮识别系统

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Text location and recognition is a vital and fundamental problem of processing images. In this paper we propose a novel system for text location and recognition focused on book covers. Our work consists of two main parts, learning-based text location and adaptive binarization guided recognition. First we extract three types of robust features from the training data provided on ICDAR2005 and utilize Ada-boost to combine these features into a powerful classifier for text regions detection and location. Second we apply the proposed adaptive binarization to process the located regions for recognition. Compared with previous works, our algorithm is robust in size, font and color of text, and insensitive for languages. In experiments, our system proved to have attractive performance.
机译:文本位置和识别是处理图像的重要而根本的问题。在本文中,我们针对书的封面提出了一种新颖的文本定位和识别系统。我们的工作包括两个主要部分,即基于学习的文本定位和自适应二值化指导的识别。首先,我们从ICDAR2005上提供的训练数据中提取出三种类型的鲁棒特征,并利用Ada-boost将这些特征组合到一个强大的分类器中,以进行文本区域检测和定位。其次,我们将提出的自适应二值化方法用于处理定位区域以进行识别。与以前的作品相比,我们的算法在文本的大小,字体和颜色方面都很健壮,并且对语言不敏感。在实验中,我们的系统被证明具有吸引人的性能。

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