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Character extraction and recognition for low-resolution color images using dominant-color-based-line-segment method

机译:基于主要颜色的线段方法的低分辨率彩色图像的字符提取与识别

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摘要

A new extraction and recognition method for low-resolution characters in complex color images has been proposed. This method generates contributivity images with region segmentation based on extracted dominant colors and recognizes characters in the multi-scale contributivity images. The contributivity images are generated using Dominant-Golor-based-Line-Segment Method which decides pixel values based on contributions of dominant colors to the pixel colors by calculating distances between the pixel colors and line-segments through pairs of dominant colors. Experiments using web images show that the proposed method has increased extraction rate from 77% to 97% and recognition rate from 62% to 85% as compared with a traditional method using k-means clustering and binary character recognition.
机译:提出了一种新的复杂彩色图像中低分辨率字符的新提取和识别方法。 该方法基于提取的显性颜色生成具有区域分割的贡献图像,并识别多尺度贡献性图像中的字符。 通过基于主机的基于大量的直升机的线段方法生成贡献性图像,该线段方法通过通过基于主显颜色计算像素颜色和线段之间的距离来基于主色谱的贡献来确定像素值。 使用Web Images的实验表明,与使用K-means聚类和二进制字符识别的传统方法相比,该方法从77%增加到97%的提取率增加到97%,并且识别率从62%到85%。

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