CODEWITHSUNDEEP
iosarkitimage-recognitioncoreml
Ketan Parmar
Ketan Parmar

Reputation: 27428

How to recognize or match two images?

I have one image stored in my bundle or in the application. Now I want to scan images in camera and want to compare that images with my locally stored image. When image is matched I want to play one video and if user move camera from that particular image to somewhere else then I want to stop that video.

For that I have tried Wikitude sdk for iOS but it is not working properly as it is crashing anytime because of memory issues or some other reasons.

Other things came in mind that Core ML and ARKit but Core ML detect the image's properties like name, type, colors etc and I want to match the image. ARKit will not support all devices and ios and also image matching as per requirement is possible or not that I don't have idea.

If anybody have any idea to achieve this requirement they can share. every help will be appreciated. Thanks:)

Upvotes: 1

Views: 2532

Answers (3)

Matthijs Hollemans
Matthijs Hollemans

Reputation: 7892

Another approach is to use a so-called "siamese network". Which really means that you use a model such as Inception-v3 or MobileNet and both images and you compare their outputs.

However, these models usually give a classification output, i.e. "this is a cat". But if you remove that classification layer from the model, it gives an output that is just a bunch of numbers that describe what sort of things are in the image but in a very abstract sense.

If these numbers for two images are very similar -- if the "distance" between them is very small -- then the two images are very similar too.

So you can take an existing Core ML model, remove the classification layer, run it twice (once on each image), which gives you two sets of numbers, and then compute the distance between these numbers. If this distance is lower than some kind of threshold, then the images are similar enough.

Upvotes: 1

Alok Subedi
Alok Subedi

Reputation: 1611

Easiest way is ARKit's imageDetection. You know the limitation of devices it support. But the result it gives is wide and really easy to implement. Here is an example

Next is CoreML, which is the hardest way. You need to understand machine learning even if in brief. Then the tough part - training with your dataset. Biggest drawback is you have single image. I would discard this method.

Finally mid way solution is to use OpenCV. It might be hard but suit your need. You can find different methods of feature matching to find your image in camera feed. example here. You can use objective-c++ to code in c++ for ios.

Upvotes: 3

Ruban4Axis
Ruban4Axis

Reputation: 841

Your task is image similarity you can do it simply and with more reliable output results using machine learning. Since your task is using camera scanning. Better option is CoreML.You can refer this link by apple for Image Similarity.You can optimize your results by training with your own datasets. Any more clarifications needed comment.

Upvotes: 2

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