图片preprocessing措施，提高识别率 [英] Image Preprocessing steps to improve the recognition rate

问题描述

我想提出一个简单的OCR Android应用使用TessBaseAPI我的项目。我做了一些像preprocessing步骤，像二值化和图象增强。但其结果是50％至60％。我们怎样才能提高识别率？

I am making a simple OCR Android App using TessBaseAPI for my project. I have done some image preprocessing steps like binarization and image inhancement. But their result is 50% to 60%. How can we improve the recognition rate?

我包括两个样本图像。

http://imageshack.us/photo/my-images/94 /1school.jpg/

http://imageshack.us/photo/my-images/43 /15071917.jpg/

推荐答案

以下补充上述命令适用于你的第二个形象：

The following additions to above command works for your second image:

-negate \
-deskew 40% \
+repage \
-crop 393x110+0+0 \

他们补充适当的倾斜校正和种植到结果的水平，从而使的tesseract的生活变得更容易一点......

They add appropriate levels of deskewing and cropping to the result, so that Tesseract's life gets a bit easier...

所以，完整的命令应该是下面的，它产生于我的系统的正确的结果：

So the complete command should be the following, which produces the correct result on my system:

convert 15071917.jpg            \
   -type grayscale              \
   -negate                      \
   -gamma 1                     \
   -contrast  -contrast  -contrast  -contrast  -contrast  -contrast  -contrast  -contrast  -contrast  -contrast  \
   -normalize -normalize -normalize -normalize -normalize -normalize -normalize -normalize -normalize -normalize \
   -despeckle -despeckle -despeckle -despeckle -despeckle -despeckle -despeckle -despeckle -despeckle -despeckle \
   -negate                      \
   -deskew 40%                  \
   +repage                      \
   -crop 393x110+0+0            \
    15071917.png                \
&&                              \
tesseract 15071917.png OUT && cat OUT.txt

  Tesseract Open Source OCR Engine v3.01 with Leptonica
    Page 0
    TESCO

这是原始图像（左）所导致的修改命令（右）的图片： ＆NBSP;

This is the original picture (left) with the resulting picture of the modified command (right):  

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