blocks|key|1770338|text|您可以在图像上指定几个区域，并检查这两个捕获图像的RGB像素值。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1770339|比如：|1770340|​|1770341|📷|atomic|offset|length|1770342|1770343|这比比较所有的像素要好。请参阅：http://www.lac.inpe.br/JIPCookbook/6050-howto-compareimages.jsp|1770344|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/68ac79a9fa7acb112c917585f8f48be7.jpg|imageAlt|1|LINK|MUTABLE|url|http://www.lac.inpe.br/JIPCookbook/6050-howto-compareimages.jsp^0|0|0|0|0|1|0|0|0|G|1R|1|0^^$0|@$1|2|3|4|5|6|7|11|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|12|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|13|8|@]|9|@]|A|$]]|$1|F|3|G|5|H|7|14|8|@]|9|@$I|15|J|16|1|17]]|A|$]]|$1|K|3|E|5|6|7|18|8|@]|9|@]|A|$]]|$1|L|3|M|5|6|7|19|8|@]|9|@$I|1A|J|1B|1|1C]]|A|$]]|$1|N|3|-4|5|6|7|1D|8|@]|9|@]|A|$]]]|O|$P|$5|Q|R|S|A|$T|U|V|-4]]|W|$5|X|R|Y|A|$Z|10]]]]

you can specify several regions on your image and check the RGB pixels value of the both captured image. 

like :

<img src="https://i.stack.imgur.com/KzvKc.jpg" alt="enter image description here">

It's better than comparison all the pixels.
see : <a href="http://www.lac.inpe.br/JIPCookbook/6050-howto-compareimages.jsp" rel="nofollow noreferrer">http://www.lac.inpe.br/JIPCookbook/6050-howto-compareimages.jsp</a>

blocks|key|1770387|text|在图片中寻找锤子(或任何其他物体)并不等于图像之间的直线像素比较。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1770388|你将需要更精细的技术来实现这一点，为艰苦的工作做好准备。|1770389|查看特征检测或级联分类器进行对象检测。|offset|length|1770390|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.opencv.org/doc/tutorials/features2d/table_of_content_features2d/table_of_content_features2d.html#table-of-content-feature2d|1|http://docs.opencv.org/doc/tutorials/objdetect/table_of_content_objdetect/table_of_content_objdetect.html#table-of-content-objdetect^0|0|0|2|4|0|7|5|1|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|S|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|T|8|@]|9|@$F|U|G|V|1|W]|$F|X|G|Y|1|Z]]|A|$]]|$1|H|3|-4|5|6|7|10|8|@]|9|@]|A|$]]]|I|$J|$5|K|L|M|A|$N|O]]|P|$5|K|L|M|A|$N|Q]]]]

looking for a hammer (or any other object) in a picture is not the same as a straight pixel comparison between images.

you'll need far more refined techniques to achieve this, prepare for hard work.

look at <a href="http://docs.opencv.org/doc/tutorials/features2d/table_of_content_features2d/table_of_content_features2d.html#table-of-content-feature2d" rel="nofollow">feature detection</a> or <a href="http://docs.opencv.org/doc/tutorials/objdetect/table_of_content_objdetect/table_of_content_objdetect.html#table-of-content-objdetect" rel="nofollow">cascade-classifiers</a> for object-detection.

blocks|key|1770427|text|图像比较是一项相当复杂的任务。首先，我想看看OpenCV库，它已经移植到Android+(和其他平台)上了。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1770428|entityMap|0|LINK|mutability|MUTABLE|url|http://opencv.org/^0|M|7|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Image comparison is a rather complicated task. As a start, I'd check out the <a href="http://opencv.org/" rel="nofollow">OpenCV library</a>, which has been ported to Android (and other platforms).

blocks|key|1492543|text|在我的一个项目中，我从相机上收集面部图像。但我需要弄清楚找到的面孔是否相似。一开始我没有识别模型，所以这意味着我不能告诉opencv来识别它们。没有数据没有分类。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1492544|因为我是为了训练一些预处理来确定标签而收集面孔的，这将是非常有帮助的。因此，我使用相对L1和有时L2距离来计算发现的人脸的相似性。检查这里的相对差异|offset|length|1492545|所以，如果你不是在谈论物体识别，比如在场景中找到所有需要付出很大努力的锤子，你可以使用这个规范的方法。通过使用这个，您可以检查您的新图像是否接近锤子、球或其他。大小将是一个问题，这可以通过金字塔方法来克服。|1492546|请注意，这甚至比中等水平的对象识别方法更糟糕。但它可以用于简单的问题，如我的预先分类的人脸图像从相机。|1492547|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.opencv.org/modules/core/doc/operations_on_arrays.html#norm^0|0|1V|2|0|0|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|S|8|@]|9|@$D|T|E|U|1|V]]|A|$]]|$1|F|3|G|5|6|7|W|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|X|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|Y|8|@]|9|@]|A|$]]]|K|$L|$5|M|N|O|A|$P|Q]]]]

In one my projects I was gathering face images from camera. But I needed to somehow figure out if faces that are found are similar. I have no recognition model at the beginning, so this means I can't tell opencv to recognize them. No data no classification. 

Since I was gathering faces for training some preprocessing to determine labels would be really helpful. So I used relative L1 and sometimes L2 distance to calculate similarity of found faces. Check what relative difference is <a href="http://docs.opencv.org/modules/core/doc/operations_on_arrays.html#norm" rel="nofollow">here</a>

So if you are not talking about object recognition like finding all kind of hammers in the scene which really requires great effort, you can use this norm approach. By using this you can check if your new image close to hammer,ball or etc. Size will be a problem, this could be overcome by using a pyramid approach. 

Note that this is even worst than a mid level object recognition approach. But it can be used for simple problems like my preclassification of face images from the camera.

I am working on the app where suppose I capture the picture of the tool like hammer or anything and later I again capture it then here I need to compare whether the tool is same so it is similar like to whether both picture are similar.

I have got one idea to do this to check the RGB pixels value of the both captured image and take the average then compare them. If both are probably near then it means both are same but that would take much time.

Any other better solution to do this in Android ?

How to check whether two image are similar in Android

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我正在开发的应用程序中，假设我捕获了工具的图片，比如锤子之类的，然后我再次捕获它，然后在这里我需要比较工具是否相同，所以它类似于这两幅图片是否相似。我有一个想法这样做，以检查RGB像素值的两个捕获图像，并采取平均值，然后比较他们。如果两者可能都在附近，那就意味着两者都是一样的，但这需要很长时间。在Android中还有其...

问如何检查两个图像在Android中是否相似
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