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KANJI RECOGNITION IN SCENE IMAGES USING DISTORTION PARAMETER ESTIMATION BASED ON SUPPORT VECTOR REGRESSION

机译:基于支持向量回归的失真参数估计,汉字识别

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Kanji character recognition in scene images is being actively researched for the purpose of indexing in image retrieval. Character recognition in scene images is the technique of detecting and recognizing characters from general images taken with a digital camera. It needs high performance since most characters lie on backgrounds that have complicated textures and are geometrically distorted because of view angles. In this paper, we propose a novel method that starts by estimating the geometric distortion of the characters through support vector regression and then recognizes the character minus the distortion. Experiments show that the proposed method has higher recognition rate due to the distortion correction.
机译:正在积极研究现场图像中的Kanji字符识别,以便在图像检索中索引。场景图像中的字符识别是从用数码相机拍摄的一般图像检测和识别字符的技术。它需要高性能,因为大多数字符位于具有复杂纹理的背景上,并且由于视角而被几何扭曲。在本文中,我们提出了一种新的方法,该方法通过支持向量回归估计字符的几何失真,然后识别字符减去失真。实验表明,该方法由于变形校正而具有更高的识别率。

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