一种有效的数字和字母字符识别方法

Yun Li, M. Xie
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引用次数: 7

摘要

提出了一种有效的数字和字母字符识别算法。我们的算法采用模板匹配,但不同于传统的模板匹配方法使用原始像素值进行匹配。我们的算法从原始图像中提取一些特征,然后得到192维的特征向量。在绘制特征之前,使用数学形态学算法对图像进行处理。然后测量样本向量和模板向量之间的欧氏距离。然后我们可以得到识别的结果。大量的实验证明,该算法具有较高的性能和鲁棒性。它可以识别相似度高的字符,如8、B、R、O和q。该算法还可以容忍图像的轻微倾斜。该算法的识别率为99.25%。
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An effective method for number and letter character recognition
An effective algorithm for number and letter character recognition is proposed in this paper. Our algorithm employs template matching, but it unlike traditional template matching method using the original pixel value to match. Our algorithm draws some features from the original image, and then obtains an eigenvector of 192 dimensions. Before drawing features, the image is disposed using math morphologic algorithm. And then measures the Euclidean distance between the sample vector and the template vector. Then we can obtain the result of recognition. A larger number of experiments prove that this algorithm own high performance and robustness. It can recognize characters which have high similarities, for example, 8, B, R, O and Q. This algorithm also tolerates the slightly tilt of the image. The recognition rate of this algorithm is 99.25%.
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