如何检测（并纠正）图像中的偏斜？ [英] How can I detect (and correct) skew in images?

问题描述

我有大量的扫描图像，它们都有些偏斜，周围有白色区域。

I have a large collection of scanned images, and they are all somewhat skewed, with a white area around them.

因此，这些图像具有矩形的颜色，周围是大的白色区域。问题是这些颜色的矩形与图像边界不平行。

So, these images have rectangles of colors, surrounded by a large white area. The problem is that these rectangles of color are not parallel to the image border.

我确信必须有一种方法可以通过编程方式检测这些颜色的矩形，以便我可以旋转图像（因此不会偏斜它），然后裁剪它，以便只留下有趣的部分。我想我不确定这个过程是什么，所以我无法在Google上搜索解决方案。

I'm sure there must be a way to programmatically detect these rectangles of color, so that I can rotate the image (thus un-skewing it) and then crop it so that just the interesting part is left. I guess I'm not really sure what this process is called, so I am having trouble searching for a solution on Google.

有没有人知道会有什么方法可以获得我开始了？我应该研究哪些图书馆？或者有助于算法的名称？

Does anyone know of an approach that would get me started? Any libraries out there that I should look into? Or the name of an algorithm that would help?

我打算在这个项目中使用Java，但我还没有真正开始，所以我对图书馆持开放态度任何语言的建议。

I am planning on using Java for this project, but I haven't really started yet, so I am open to library suggestions in any language.

推荐答案

• 边界检测


• 霍夫变换（如果图像上的所有矩形具有相同的偏斜）


• 矩形轮廓检测（连通分量轮廓，然后最小区域边界矩形）



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