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A Novel Label Protuberant Characters Recognition Method Based on WPT and Improved SVD

机译:一种基于WPT和改进SVD的新型标签突出字符识别方法

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To recognize protuberant characters on the labels, a novel recognition method based on gray image using wavelet packet transform (WPT) and improved Singular Value Decomposition (SVD) is suggested. The images are decomposed by WPT, and then the singular values (SVs) feature and projection feature of approximation images obtained through the above process are combined to form a new eigenvector using weighting coefficient. And the comparisons of recognition experiments are carried out using Euclidean distance. This method not only makes full use of many excellent properties of the SVs feature, but also overcomes the shortcomings of missing useful niformation and many other problems caused by image binarization. Experiments confirm that the method could effectively improve the recognition rate of characters, and has much better robustness.
机译:为了识别标签上的突起字符,提出了一种基于小波包变换(WPT)和改进的奇异值分解(SVD)的基于灰度图像的新颖识别方法。通过WPT分解图像,然后通过上述过程获得的奇异值(SVS)特征和投影特征和通过上述过程获得的近似图像的特征以形成使用加权系数的新特征向量。并且使用欧几里德距离进行识别实验的比较。这种方法不仅可以充分利用SVS特征的许多优异的性质,而且还克服了缺失有用的痣的缺点以及图像二值化引起的许多其他问题。实验证实,该方法可以有效地提高人物的识别率,并具有更好的稳健性。

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