比较旋转的图像 [英] Comparing rotated images

问题描述

我正在寻找一种比较几乎相同(95％+相似度)但可以绕中心轴旋转的图像的方法.

I'm looking for a way to compare images that are almost identical (95%+ similarity) but that could be rotated around a central axis.

我是整个计算机图形/视觉领域的新手，并且不确定是否有现成的工具或系统，或者这是否是可以询问的正确堆栈.

I'm new to the whole computer graphics/vision field, and not really sure if there is a ready built tool or system for it, or even if this is the right stack exchange to ask on.

目前，我正在研究使用C#生成位图直方图，然后通过Panda运行它进行分析，并根据直方图的相似性对图像进行理想分组，尽管我听说过类似OpenCv + tesseract的内容可行的选择.

Currently, I'm investigating using C# to generate a bitmap histogram, then running it through Panda for analysis and to ideally group the images based on the similarity of histograms, though I've heard something like OpenCv + tesseract may be a viable alternative.

推荐答案

您可以使用特征点提取比较图像相似性，并使用旋转和比例不变算法来进行匹配.

You can compare image similarity using feature point extraction and matching using rotation and scale invariant algorithms.

OpenCV中已经提供了旋转不变特征匹配算法- SIFT ，SURF，但这些已获得专利，因此，如果要在商业上使用它们，则必须付费.

Already rotation invariant feature matching algorithms are available in OpenCV - SIFT ,SURF but these are patented so you have to pay if you want to use them commercially.

幸运的是，可以使用SIFT或SURF的有效替代方法，即 ORB (定向的FAST和旋转的简报)

Fortunately an efficient alternative to SIFT or SURF is available namely ORB (Oriented FAST and Rotated BRIEF)

这些算法在大多数图像中都可以正常工作，除了一些像文档图像一样.

These algorithms work fine in most of the images except a few like document images.

PS:如问题中所述(OpenCV + tesseract)，也可以用于文档图像，方法是使用 Tesseract 库(开源OCR引擎)

PS: As mentioned in the question (OpenCV + tesseract) alternatively can be used for document images by extracting the text contents in the image using Tesseract library(Opensource OCR engine)

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