I am going to write a mobile application that recognizes images within a closed
ID: 658835 • Letter: I
Question
I am going to write a mobile application that recognizes images within a closed target group. I guess the group contains 20 to 50 comic-like images like this.
The application reacts if any of those targets are captured by the camera of the device. That's it.
There are some constraints, though.
It should recognize rotated targets.
It should recognize those with the different perspectives and levels of light.
If it can handle with obstruction like fingers, I'll be happy with that. (optional)
It should be easy to train. (optional)
I'd prefer inaccurate but fast solutions. (no more than 3 seconds, maybe?)
I don't have sufficient time for the task and am kind of new to image-processing, so starting with OpenCV is time-consuming, apparently.
I'm looking forward to your suggestions.
Plus, the solutions do not have to be free.
Edit:
In terms of our budget, I may have to ask my non-tech boss who doesn't likely know the common price. Just give me suggestions / offers regardless of the price then he's going to pick one.
Explanation / Answer
You should have a look at the Moodstocks SDK. It fits most of your requirements:
it's robust to lightning and perspective changes,
it tolerates partial occlusion, for example by fingers,
it require no training at all: you just upload (index) an image to make it instantly recognizable,
it's extremely fast: the image matching is done locally, so on a modern smartphone you'll get a result in far less than 300ms.
The only issue is with the robustness to rotation: the Moodstocks SDK only supports small rotation (~30
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