I'm building an Android app that has to identify, in realtime, a mark/pattern which will be on the four corners of a visiting card. I'm using a preview stream of the rear camera of the phone as input.
I want to overlay a small circle on the screen where the mark is present. This is similar to how reference dots will be shown on screen by a QR reader at the corner points of the QR code preview.
I'm aware about how to get the frames from camera using native Android SDK, but I have no clue about the processing which needs to be done and optimization for real time detection. I tried messing around with OpenCV and there seems to be a bit of lag in its preview frames.
So I'm trying to write a native algorithm usint raw pixel values from the frame. Is this advisable? The mark/pattern will always be the same in my case. Please guide me with the algorithm to use to find the pattern.
The below image shows my pattern along with some details (ratios) about the same (same as the one used in QR, but I'm having it at 4 corners instead of 3)
I think one approach is to find black and white pixels in the ratio mentioned below to detect the mark and find coordinates of its center, but I have no idea how to code it in Android. I looking forward for an optimized approach for real-time recognition and display.
Any help is much appreciated! Thanks
Detecting patterns on four corners of a visiting card:
Assuming background is white, you can simply try this method.
Needs to be done and optimization for real time detection:
Yes, you need OpenCV
Here is an example of real-time marker detection on Google Glass using OpenCV
In this example, image showing in tablet has delay (blutooth), Google Glass preview is much faster than that of tablet. But, still have lag.
Related
i'm trying to do a simple AR scene with NFT image that i've created with genTextData. The result works fairly well in unity editor, but once compiled and run on an android device, the camera resolution is very bad and there's no focus at all.
My marker is rather small (3 cm picture), and the camera is so blurred that the AR cannot identify the marker from far away. I have to put the phone right in front of it (still verrrrryy blurred) and it will show my object but with a lot of flickering and jittering.
I tried playing with the filter fields (Sample rate/cutoff..), it helped just a little bit wit the flickering of the object, but it would never display it from far away..i always have to put my phone like right in front of it. The result that i want should be: detecting the small marker (sharp resolution or/and good focus) from a fair distance away from it..just like the distance from your computer screen to your eyes.
The problem could be camera resolution and focus, or it could be something else. But i'm pretty sure that the AR cannot identify the marker points because of the blurriness.
Any ideas or solutions about this problem ?
You can have a look here:
http://augmentmy.world/augmented-reality-unity-games-artoolkit-video-resolution-autofocus
I compiled the Unity plugin java part and set it to use the highest resolution from your phone. Also the auto focus mode is activated.
Tell me if that helps.
What I am doing is attempting to using EMGU to perform and AbsDiff of two images.
Given the following conditions:
User starts their webcam and with the webcam stationary takes a picture.
User moves into the frame and takes another picture (WebCam has NOT moved).
AbsDiff works well but what I'm finding is that the ISO adjustments and White Balance adjustments made by certain cameras (even on Android and iPhone) are uncontrollable to a degree.
Therefore instead of fighting a losing battle I'd like to attempt some image post processing to see if I can equalize the two.
I found the following thread but it's not helping me much: How do I equalize contrast & brightness of images using opencv?
Can anyone offer specific details of what functions/methods/approach to take using EMGUCV?
I've tried using things like _EqualizeHist(). This yields very poor results.
Instead of equalizing the histograms for each image individually, I'd like to compare the brightness/contrast values and come up with an average that gets applied to both.
I'm not looking for someone to do the work for me (although code example would CERTAINLY be appreciated). I'm looking for either exact guidance or some way to point the ship in the right direction.
Thanks for your time.
I need to scan a special object within my android application.
I thought about using OpenCV but it is scanning all objects inside the view of the camera. I only need the camera to regognize a rectangular piece of paper.
How can i do that?
My first thought was: How do barcode scanners work? They are able to regognize the barcode area and automatically take a picture when the barcode is inside a predefined area of the screen and when its sharp. I guess it must be possible to transfer that to my problem (tell me if im wrong).
So step by step:
Open custom camera application
Scan objects inside the view of the camera
Recognize the rectangular piece of paper
If paper is inside a predefined area and sharp -> take a picture
I would combine this with audio. If the camera recognized the paper make some noice like a peep or something and the more the object is fitting the predefined area the faster the peep sound is played. That would make taking pictures for blind people possible.
Hope someone got ideas on that.
OpenCV is an image processing framework/library. It does not "scan all objects inside the view of the camera". By itself it does nothing and yet it gives the use of a number of useful functions, many of which could be used for your specified application.
If the image is not cluttered and nothing is on the paper, I would look into using edge detection (i.e. Canny or similar) or even colour blobs (even though colour is never a good idea, if your application is always for white uncovered paper, it should work robustly).
OpenCV does add some overhead, but it would allow you to quickly use functions for a simple solution.
Maybe a comparison of pictures best illustrate the problem.
This is the original picture:
Using Android SDK, I managed to take this photo from my Android phone:
You may see that, there are lots of gray strips on the photo.
Although the main shapes are there, for I'm processing these photos on an image recognition project, these gray stripe completely ruined the results.
It (Edit: does not ) seems that the built-in photo app would automatically eliminate them, but I don't know how to do it manually in my app. Seems that this is caused by display having a different refresh rate.
What you're seeing is happening because cameras have a small advantage over the human eye when taking the photo.
The refresh rate for most displays is 50Hz or 60Hz, which is too fast for our eyes to notice.
However, a camera sensor takes the image much faster than the human eye, and can see the scan lines created by the refreshing of the image on the display. You can work around this by using a longer exposure time, closer to the human eyes' speed, but you may not be able to control that on most Android devices.
I suggest you use your operating system's inbuilt screenshot utility instead.
I am looking for some kind of auto trim/crop functionality in android.
Which detects a object in captured image and creates a square box around object for
cropping. I have found face detection apis in android, but my problem is captured images are documents/pages not human faces so how can I detected documents or any other object from captured picture.
I am thinking of any algorithms for object detection or some color detection. Is there any apis or libraries available for it.
I have tried following link but not found any desired output.
Find and Crop relevant image area automatically (Java / Android)
https://github.com/biokys/cropimage
Any small hint would also help me alot. Please help. Thanks in advance
That depends on what you intend to capture and crop, but there are many ways to achieve this. Like littleimp suggested, you should use OpenCv for the effect.
I suggest you use edge-detection algorithms, such as Sobel, and perform image transformation on it with, for example, a Threshold function that will turn the image into a binary one (only black and white). Afterwards, you can search the image for the geometric shape you want, using what's suggested here. Filter the object you want by calculating the detected geometric figure's area and ratio.
It would help a lot to know what you're trying to detect in an image. Those methods I described were the ones I used for my specific case, which was developing an algorithm to detect and crop the license plate from a given vehicle image. It works close to perfect and it was all done by using OpenCV.
If you have anything else you'd like to know, don't hesitate to ask. I'm watching this post :)
Use OpenCV for android.
You can use the Watershed (Imgproc.watershed) function to segment the image into foreground and background. Then you can crop around the foreground (which will be the document).
The watershed algorithm needs some markers pre-defining the regions. You can for example assume the document to be in the middle of the image, so create a marked region in the middle of the image to get the watershed algorithm started.