如何检查图像是否包含脸部并且其是否清晰可见
我不确定这是否可以解决，但我想无论如何我都会问。
在我的公司，我们负责大规模的招生营，由 5 到 10 人组成的小团队前往村庄招收人员。注册过程包括输入一些数据、采集指纹以及使用网络摄像头拍摄最终用户的照片。可以理解的是，注册是由我们将活动外包给的外部供应商完成的。
由于记录数量巨大，尝试手动验证记录会使整个过程变慢。因此，我们已经自动化了尽可能多的事情，除了一件事，那就是检查使用网络摄像头拍摄的照片质量是否良好。
我知道，“优质”是一个模糊的术语，不能转化为基于软件的解决方案。然而，在尝试为自己定义“良好质量”时，我发现了这一点： http://en.wikipedia.org/ wiki/Image_quality
现在，最后回到我的问题，这些图像质量检查的哪些部分可以自动化。
注意：照片将以邮票大小打印在智能卡上。在 300 DPI 下，它们的分辨率仅为 100x125 像素。
干杯， 拉古
I am not sure if this is solveable, but I though I will ask anyway.
In my company we deal with massive enrollment camps where small teams of 5 to 10 people go to a village and enroll people. The enrollment involves entering some data, capturing fingerprints and taking a mug-shot of the end-user using a webcam. Understandably enrollment is done by external vendors to whom we have outsourced the activity.
Since the no of records are overwhelmingly large trying to verify records manually is making the entire process slow. So we have automated as many things as possible except for one thing, which is to check if the photo captured using the webcam is of good quality.
I know, "Good Quality" is a vague term which cannot be translated to a software based solution. However, while trying to define Good Quality to myself, I found this: http://en.wikipedia.org/wiki/Image_quality
Now, finally coming to my question, what parts of these image quality checks can be automated.
Note: The photographs will be printed on a smart-card in stamp-size. They would barely be 100x125 pixels at 300 DPI.
Cheers,
Raghu
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维奥拉-琼斯算法是一个经典算法。 在这里您可能会找到一篇有关其实现的论文，但你会发现很多资源。
我喜欢的图片：
在这里您可能会找到实现 alg 的 .Net 框架。 （免费）
Ps：请注意，某些外星生命体可能会返回误报。
The Viola-Jones algorithm is a classic. Here you may find a paper about its implementation, but you'll find many resources out there.
My preferred picture:
Here you may find a framework for .Net implementing the alg. (it's free)
Ps: Note that some extraterrestrial lifeforms may return false positives.
机械土耳其人？ :)
Mechanical Turk? :)
openCV 库有一些很棒的用于检测人脸的代码。您可以使用 openCV 人脸检测作为图像质量的阈值来进行配置 - 如果它成功检测到人脸，它可能相当不错？
http://sourceforge.net/projects/opencvlibrary/
The openCV library has some great code for detecting faces. You could rig something up using the openCV face detection as a threshold for image quality - if it successfully detects a face, it's probably pretty good?
http://sourceforge.net/projects/opencvlibrary/
人脸检测是一个非常活跃的研究课题和论文，一直在 ECCV、ICCV 等计算机视觉会议上发表。今年的 ECCV2010 甚至还举办了人脸检测研讨会。所以，是的，它可以在合理的程度上解决。
如果我是你，我会构建一些非常简单的东西，但可以应对光照、肤色和框架变化的基本要求。如果你知道这些照片通常都是照片，那么你就不需要像维奥拉·琼斯这样复杂的东西了。您应该构建一个面部照片验证系统（这张照片看起来像一张照片吗？），而不是一个面部检测系统（这张图像中的面部在哪里？）。
首先，只需检查图像中的基础知识 - 例如使用强度直方图来确保照明正常（不要太亮；太暗），图像具有对比度（不同的阴影）等。
然后，您可以构建一张脸/mugshot 验证系统 - 构建一个像经典的“特征脸识别' 论文，然后确定每个照片是否足够像该子空间中的照片。 （这是相当简单的技术，网上有很多代码可以做到这一点）。
Face detection is a very active research topic and papers and published all the time in computer vision conferences such as ECCV, ICCV. In this years ECCV2010 there was even a workshop on face detection. So, yes it is solveable to a reasonable degree.
If I were you I'd build something pretty simple but that can cope with the essentials of lighting, skin colour, and framing variance. You won't need something sophisticated like Viola-Jones if you know the pictures are generally going to be mugshots. You should build a mugshot verification system (does this picture look like a mugshot?) rather than a face detection system (where are the faces in this image?).
Firstly, just check the basics in the image - for example using an intensity histogram to ensure the lighting is ok (not too bright; too dark), that the image has contrast (different shades), etc.
Then, you could build a face/mugshot verification system - build a face space like in the classic 'Eigenfaces for Recognition' paper, and then determine if each mugshot is sufficiently like a mugshot in this subspace. (This is fairly simple technique and much code is available on the web to do it).