Im using Apple ARKit Scanner app to scan objects and then detect those objects. I'm wondering is it possible to scan two identical objects but of different colours and be able to detect the difference.
I suspect the scanner generates reference points on the object which are then detected but is there a way to get it to pick up colour difference?
Example would be two trainers of the same style but one black and one white.
I'm thinking maybe an ARReferenceImage may be a better option as I don't really need all round detection from different angles?
Thanks
ML-algorithm of ARKit detects a pre-scanned objects (in .arobject container) in black-and-white scheme, not in RGB colour scheme. If you scan two absolutely similar volumetric objects but with a different colour scheme, there's no any guarantee ARKit will recognise each of them successfully.
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I want to detect shape and then describe it (somehow) to compare it with server data.
So the first question is, is it possible to detect shape like blob with ARKit?
To be more specific, let's describe my usecase generally.
I want to scan image by phone, get the specific shape, send it on server, compare two images on server (server image is the real one, scanned image would be very similar) and then send back some data. I am not asking about server side, the only question about server side is what should I compare - images using OpenCV, some mathematical description of both images and try to find similarity, etc.).
If the question is hard to understand, let's split it on two easy questions:
1) How to scan 2D object by iPhone and save it (trim the specific shape from its background when object is black and background white).
2) Describe scanned object for comparision with almost the same object.
ARKit has no use here.
You will probably need a lot of CoreImage (for fixing perspective distortion and binarization) and OpenCV logic.
Perhaps Vision can help you a little bit with getting ROI from the entire frame, especially if the waveform image is located in some kind of rectangle.
Perhaps you can train a custom ML model that will recognize specific waveforms or waveforms in general to use with Vision.
In any case, it is not a trivial task.
For example, I have a CGImageRef and I want to shift all pixels which are red to orange. Or to put it in other words: I want to apply a value function on every pixel in an image, which modifies the pixel based on the RGBA values it has. So the value function would calculate the new component values for that pixel based on the current component values and some algorithm applied to it.
I know how I could code that by hand with about 100 lines of code, but I wonder if there is a easier and maybe even faster way?
I believe Brad Larson has mentioned somewhere that things like this can be done on the GPU easily and fast. However, I must support iOS 3.2 so it should not get too fancy.
Would be happy about any ideas.
Thanks!
As far as I know there are no built in functions to achieve what you want.
The easiest way to get GPU acceleration when doing custom image manipulations on the pixel level is using the Accelerate.framework. Accelerate will use the 'best execution path' based on available hardware.
However... the port to iOS was only done for iOS4
(disclaimer: I have little to no experience nor knowledge of everything that's possible in OpenGL, so take my answer as limited within the Core Graphics realms of iOS)
I am working on car parking system project. For that, I would like to detect the presence of a car.
Can anybody tell me how I can accomplish this using MATLAB?
Also, what is the algorithm for detecting a car?
There's a whole world of methods for object detection in images. You need to learn a little bit about image processing to solve this problem. I suggest you read about template matching or more generally about Object recognition. Specifically for car detection, if you know they will be seen at a certain angle (head on, for example) i'd try Viola-Jones detection which is implemented in OpenCV as haar-based feature cascade detection. Although OpenCV is not a matlab library, you can probably find something in matlab's image processing toolboxes that does a similar job (or interface into OpenCV)
Background subtraction would be a simple place to start.
In a nutshell:
Can capture an image of your empty parking lot. This is your reference image.
Compare the current image of your parking lot with the reference image. The parts that are different will be of interest.
Problems:
You need to keep updating your reference image to stay current with the conditions (e.g. day, night, cloudy, raining). Sometimes this may not be possible, because your reference image needs to have no cars in it for the approach to work.
Moving things in the background (like trees shaking in the wind) will come up as false positives
Have you considered using 3D/stereoscopic imaging in addition to using 'normal' images? If yes you could open up a whole new world of methods and intelligent tricks to remove objects based upon their distance to the camera. Then, any object that is a certain, fixed distance from the camera (e.g. your background) is easily removable and you can just process the new parts of the image (e.g. cars).
If this interests you I can supply you with an algorithm I have developed to detect animals in a livestock pen, which is a similar concept.
Being a complete noob in iPhone development, I was wondering what would be the best way to define regions in an Image (for interaction ). So far I've got 2 ideas :
use CGpath to basically draw the areas that I`m interested in but I quickly can see it becoming tedious on complex graphics .
use a Color coded layer with regions containing different RGB values and return those as my regions .
Are those sensible approaches ?
Depends on what you mean by interaction and whether you want the regions to be visible to the user.
A simple approach would be to just add UIButton's above your image. They can be transparent and any size (rectangular) that you like. Or they can contain images or colors to be visible to the user.
If you need arbitrary shapes then this solution won't be useful to you.
how to do morphing of two images in iphone programming.?
Your question is not iphone related.. the kind of algorithm you are looking for is language-agnostic since it just work with images.
By the way it's quite complex to morph two images, usually you have to
embed a grid of points over the two images that links characteristics that should be morphed. For example if you have two faces you would use a grid that connects eyes, the mouth, ears, the nose, the edge of the face and so on: these two grid tells the morpher how to "translate" a point into another one while blending the two images
the previous step can be done automatically (with specific software) or by hand. more points you place better will be your results
then you can do the real morphing sequence: basically you do an interpolation between the two images (in which the parameter that you use will decide how much will be the final risult similar to the first or the second image)
you should also apply some blending effect to actually create a believable result, always using a parametric function according to the morphing position
You can use UIView animation to transition from one UIView to another. This should provide some sort of lame morphing.
You can use XMRM, which is written in C++: http://www.cg.tuwien.ac.at/~xmrm/
There is no image morphing API in the iOS SDK.
No, there isn't an API for it. You'll have to do it yourself.
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