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Deformable Grid in Image Recognition

机译:图像识别中的可变形网格

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摘要

Deformable template has been shown to significantly improve the performance of image recognition for difficult tasks such as character recognition, digit recognition, and trademark recognition etc. However, it is often time-consuming. Grid feature is a popular feature extraction scheme in image recognition. Here we propose deformable grid for image recognition. Unlike deform-able template where deformation is applied to image, deformation is applied to grid in deformable grid. Because the number of grid is much less than that of image, our method is very timesaving comparing to deformable template. The approximate equality of deformable template and deformable gird is also shown. We tested our method in two image recognition experiments, namely, trademark recognition and off-line Chinese character recognition. We obtained improvement in recognition rate by 6.0% in first experiment, and 5.8% in second one.
机译:可变形的模板已经显示出可以显着提高图像识别在诸如字符识别,数字识别和商标识别等困难任务上的性能。但是,它通常很耗时。网格特征是图像识别中流行的特征提取方案。在这里,我们提出用于图像识别的可变形网格。与将变形应用于图像的可变形模板不同,将变形应用于可变形网格中的网格。由于网格数量远少于图像数量,因此与可变形模板相比,我们的方法非常省时。还显示了可变形模板和可变形围网的近似相等性。我们在两个图像识别实验中测试了我们的方法,即商标识别和离线汉字识别。第一个实验的识别率提高了6.0%,第二个实验的识别率提高了5.8%。

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