Hi guys,
I'm working again on a shelf detector (detects product on a shelf and cut them into images) but the last approach (using hist inspection, as mentioned in my previous question) did not suited for my purposes.
So, my tutor told me to try to use an object detection algorithm like SIFT or SURF and use the features extracted from a template image to detect other products.
Because the products differ in their "contents", i.e. logos and drawings on their covers, my idea is to use object detection and then tell to do opencv something like this:
1)get descriptors 2)match all the part of the test image that has a % of keys (not 100% match) > of TOT%
so I have to write an algorithm that selects objects in the test image that has a % of keys matching the template image.
Is this possible with opencv?
Thank you in advance, Panc