基于GCM与RFH的文本图像联合识别

United Recognition of Document Images Based on GCM and RFH

  • 摘要: 为了更好地识别文本图像,分析了基于灰度共生矩阵的特征在文本图像识别中的盲点,提出利用矩形框直方图来形成新的特征,以此联合识别文本图像.实验证实本文方法平均识别率高达95.96%,且虚报率仅为0.92%,优于基于灰度共生矩阵的识别.

     

    Abstract: In order to recognize document images (DIs) more efficiently, this paper analyzes the blind point of the gray co-occurrence matrix based features in document image recognition, and presents novel features based on rectangle frame histogram (RFH) for united recognition of document images. Experiments show that the proposed method is superior to the GCM (gray co-occurrence matrix) based method in terms of recognition rate (95.96%) and false alarm rate (0.92%).

     

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