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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的场景图像汉字识别

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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:为了索引图像检索中的目的,正在积极研究场景图像中的汉字字符识别。场景图像中的字符识别是一种从数码相机拍摄的普通图像中检测和识别字符的技术。它需要高性能,因为大多数字符都位于纹理复杂且由于视角而几何变形的背景上。在本文中,我们提出了一种新方法,该方法首先通过支持向量回归估计字符的几何变形,然后识别出减去变形的字符。实验表明,该方法由于失真校正,具有较高的识别率。

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