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Text localization using valid optical flow for recognition of slab numbers

机译:使用有效的光学流进行文本本地化,以识别板号

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The goal of this study is to develop a new algorithm to determine the placement of text in images using two consecutive frames. The algorithm consists of two steps: detection of top and bottom boundaries (TBB) and determination of left and right boundaries (LRB) of the texts. For accurate detection of the LRB, several algorithms are proposed in this paper. First, morphological and geometrical information of the letters is used to identify TBB. Next, coarse LRB are determined using an optical flow, which is rendered by the combined methods of Lucas/Kanade and Horn/Schunck algorithms in video sequences. Finally, the texts are localized from the image based on optical flow field information. Experimental results of the text localization have 95.7 % recall. The algorithm is developed in a module and can hence be embedded in a steel product management system easily.
机译:本研究的目标是开发一种新的算法,用于使用两个连续帧确定图像中的文本的位置。该算法由两个步骤组成:检测顶部和底部边界(TBB)和文本的左边界(LRB)的确定。为了精确地检测LRB,本文提出了几种算法。首先,使用字母的形态和几何信息来识别TBB。接下来,使用光学流来确定粗LRB,其通过视频序列中的卢卡斯/ kanade的组合方法和喇叭/苏克克算法呈现。最后,文本基于光流场信息从图像本地化。案文本地化的实验结果召回了95.7%。该算法在模块中开发,因此可以轻松嵌入钢材产品管理系统中。

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