If you're finding the objects automatically, you can write an algorithm to do that. If you're doing it manually, your corpus isn't going to be big enough, and I can just pay people to enumerate them.
Plus, for all of the examples I see on your page, you can just find objects of interest, which is fairly trivial, and that's probably going to be what you're looking for.
You're right about certain images having easily distinguished objects-of-interest. In the future, running a routine to weed those easy ones out will stop any being solvable by bots. And also, as with any other captcha, paying other humans to validate themselves for you will always be an issue.
We validate users' inputs against a pool of manually-entered data. Because we collect a pair of annotations for each submission, one is used to verify the user, and the other is collected against an un-annotated image. As annotations are collected for new images, they are synthesized to expand the pool of annotated images.