We present a new CAPTCHA which is based on identifying an image’s upright orientation. This task requires analysis of the often complex contents of an image, a task which humans usually perform well and machines generally do not.
Given a large repository of images, such as those from a web search result, we use a suite of automated orientation detectors to prune those images that can be automatically set upright easily.
We then apply a social feedback mechanism to verify that the remaining images have a human-recognizable upright orientation. The main advantages of our CAPTCHA technique over the traditional text recognition techniques are that it is language-independent, does not require text-entry (e.g. for a mobile device), and employs another domain for CAPTCHA generation beyond character obfuscation. This CAPTCHA lends itself to rapid implementation and has an almost limitless supply of images.
We conducted extensive experiments to measure the viability of this technique.
We ensure that our CAPTCHA can not be defeated by state-of-the-art orientation detection systems by using those systems to filter images that can be automatically recognized and oriented.
In contrast to traditional text based CAPTCHAs which introduce more noise and distortion as automated character recognition improves, we currently do not need to alter or distort the content of the images.
As advances are made in orientation detection system, these advances will be incorporated in our filters so that those images that can be automatically oriented are not presented to the user. The use of distortions may eventually be required.
Looks like a good way to provide CAPTCHA without the annoyance of squinting to see if that's a P or an R behind that other letter.
I look forward to checking it out.
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