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Linux上的图像处理和识别实现。 如何?

[英]Image process & recognition implementation on Linux. How to?

Usually I develop image processing or recognition programs on windows. 通常我会在Windows上开发图像处理或识别程序。 But I got a customer who requires me to implement one on Linux platform. 但我有一位客户要求我在Linux平台上实现一个。

Because his platform is embedded system, I don't know for sure that OpenCV would be available. 因为他的平台是嵌入式系统,所以我不确定OpenCV是否可用。 Could anyone give me some clue to get started? 有人能给我一些开始的线索吗?

You can package OpenCV with your application. 您可以将OpenCV与您的应用程序打包在一起。

The word 'embedded' makes me nervous - image recognition can be very computationally expensive. “嵌入式”这个词让我感到紧张 - 图像识别的计算成本非常高。 You may need to roll your own code to fit the target constraints. 您可能需要滚动自己的代码以适应目标约束。

The starting point of your own code is likely to implement a Haar-like recogniser. 您自己的代码的起点可能会实现类似Haar的识别器。 This is of course what you'd likely be using OpenCV to do. 这当然是你可能正在使用OpenCV做的事情。 A more ambitious recogniser is HOG . 一个更雄心勃勃的认知者是HOG Here 'sa nice comparison of them. 是一个很好的比较。

OpenCV is in standard repositories for Ubuntu and/or Debian Linux. OpenCV是Ubuntu和/或Debian Linux的标准存储库。 As such it should run on many processors including ARM. 因此,它应该在许多处理器上运行,包括ARM。 If it runs a full Debian, it is a matter of apt-cache search opencv , then install the modules you want via apt-get install . 如果它运行完整的Debian,那就是apt-cache search opencv ,然后通过apt-get install你想要的模块。

The big gotcha is the embedded part. 最重要的是嵌入式部分。 If it doesn't run a full Linux, then you may end up compiling for a very long time. 如果它没有运行完整的Linux,那么你最终可能会编译很长时间。 Cross your fingers it runs a full Linux (like Debian.) 交叉你的手指它运行一个完整的Linux(像Debian。)

Adaboost should be a good fit for use as a learning algorithm. Adaboost应该非常适合用作学习算法。 Paul Viola and Michael Jones have an interesting paper on efficient face detection using Adaboost and Haar classifiers. Paul Viola和Michael Jones有一篇关于使用Adaboost和Haar分类器进行高效人脸检测的有趣论文 There's a lot of math there, but it's worth reading. 那里有很多数学,但值得一读。

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