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A new binarization method for high accuracy handwritten digit recognition of slabs in steel companies

机译:钢铁公司板坯高精度手写数字识别的新二值化方法

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Handwritten digit recognition plays a crucial role in various automatic systems and industries nowadays. In steel companies, the code digits written on slab forehead should be recognized with high accuracy because these codes are used for determination of suitable thickness of steel slabs in rolling procedure. Because of special artifacts exist in these kinds of images such as color sagging, faint colors, and color separation, most of the common digit recognition algorithms have low accuracy in recognition of code digits. In this paper, a new two stage algorithm is proposed in order to reach high accuracy in determination of the handwritten codes written on slabs forehead and are corrupted by color sagging, faint colors and color separation. Applying our proposed algorithm on a dataset of images of slabs in Isfahan Steel Company shows that accuracy of the algorithm is 89.12% which is much higher than common and recently proposed algorithms.
机译:如今,手写数字识别在各种自动化系统和行业中都扮演着至关重要的角色。在钢铁公司中,板坯前额上的代码数字应被高精度地识别,因为这些代码用于确定轧制过程中钢板的合适厚度。由于这些类型的图像中存在特殊的伪影,例如颜色下垂,微弱的颜色和颜色分离,因此大多数常见的数字识别算法在识别代码数字时均具有较低的准确性。本文提出了一种新的两阶段算法,以期在确定书写在平板前额上的手写代码时达到较高的准确性,并且由于颜色下垂,模糊的颜色和颜色分离而受到破坏。将我们提出的算法应用于伊斯法罕钢铁公司的板坯图像数据集表明,该算法的精度为89.12%,远高于最近提出的常见算法。

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