真实时间图像处理(OCR) [英] Real TIme Image Processing (OCR)

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本文介绍了真实时间图像处理(OCR)的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我计划开发一个类似 Word Lens <的应用程序一>。任何人都可以建议我可以使用的好图书馆吗?或任何人解释Word Lens App背后的技术?是卷轴时间图像匹配还是OCR?我知道一些图像处理库,如OpenCv,tesseract ...非常感谢任何帮助...

I am planing to develop an app like Word Lens. Can any one suggest a good library that I can use? or any one explain technology behind the Word Lens App? is it reel time image matching or OCR? I know some image processing library like OpenCv, tesseract...Any help is greatly appreciated...

推荐答案

我是一个Word Lens的创作者。虽然有一些OCR库(如tesseract),但我们决定自己创建,以获得更好的结果和性能。我们的通用算法如下:

I'm one of the creators of Word Lens. Although there are some OCR libraries out there (like tesseract), we decided to make our own in order to get better results and performance. Our general algorithm goes like this:


  1. 从相机复制图像并获取其灰度组件

  2. 平整图像,使文字在背景中清晰突出

  3. 在看起来像角色的东西周围画出框。句子

  4. 做OCR:将每个方框中的像素与字符数据库相匹配 - 这实际上非常难!

  5. 将字符收集到单词中,在字典中查找(这也很难,因为在OCR中会出现错误)

  6. 将结果绘制回图像

  1. copy the image from the camera and get its grayscale component
  2. level out the image so the text stands out clearly against the background
  3. draw boxes around things that look like characters & sentences
  4. do OCR: match the pixels in each box against a database of characters -- this is actually pretty hard!
  5. collect the characters into words, look up in a dictionary (this is hard too, because there will be mistakes in the OCR)
  6. draw the results back onto the image

图像匹配本身并不够好,因为那里有各种各样的字体,单词和语言。

Image matching by itself is not good enough, because of the huge variety of fonts, words, and languages out there.

OpenCV是一个很好的图书馆,可以启动和运行,并了解更多有关计算机视觉的信息。我建议建立他们的例子,并在那里玩。玩得开心!

OpenCV is a great library to get up and running with, and to learn more about computer vision in general. I would recommend building off their examples, and playing around there. Have fun!

这篇关于真实时间图像处理(OCR)的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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