Is there any way to get text data present in .jpeg or .png file which is captured by camera?
For example-
If i captured debit card by device camera then how to get debit card number or card holder name present on it from captured photo.
Basically, as already suggested above, you are to plunge into the science of optical recognition. These are quite complex algorithms that analyze pixels of an image and try to 'see' some text or, let's say, faces in the images. This objective, obvious for a human eye and mind, is quite complex especially considering that the image may have been shot with some particular lighting (back light or side light), with right or wrong white balance, etc.
Despite the whole complexity, there is good news: Google has provided a special library that does exactly that: recognizes texts, bar codes and faces. It is called Mobile Vision
Even without knowing the recognizing algorithms, you basically initiate this library and then feed your images to these algorithms with Face API, Barcode API or Text API. And then after the processing within that library you are given whatever was found by those algorithms. It's a kind of Magic :)
Useful links here:
Tutorial with Text API
The code sample of the app using Text API
Related
Are any of the current text capture APIs (e.g. Google's Text API) fast enough to capture text from a phone's video feed, and draw a box that stays on the text even as the camera moves?
I don't need fast enough to do full OCR per-frame (though that would be amazing!). I'm just looking for fast enough to recognize blocks of text and keep the bounding box displayed in sync with the live image.
There are two major options for good results. They are both C++ but there are wrappers. I've personally played with OpenCV for face recognition and the results were promising. Below links with small tutorials and demos.
OpenCV
Tessaract by Google
Firebase
onDeviceTextRecognizer is simple and working for me.
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.
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 just need some guide on how to detect a marker and make an output text.. for ex: a marker with an image of a dog , when detected, i have an output text "DOG" in a textfield .. can someone help me with my idea? oh, btw which one is more effective to use nyartoolkit or andar for my idea?thanks:) need help..!
What you're looking for isn't augmented reality, it's object recognition. AR is chiefly concerned with presenting data overlaid on the the real world, so computation is devoted each frame to determining the position relative to the camera of the object. If you don't intent to use this data, AR libraries may be an inefficient. That said...
AR marker tracking libraries usually find markers by prominent features like corners, and can distinguish markers by binary patters encoded inside the marker, or in the marker's borders. If you're happy with having the "dog" part encoded in the border of a marker, there are libraries you can use like Qualcomm's AR development kit. This library, and Metaio's Unifeye mobile can also do natural feature tracking on pre-defined images. If you're happy with being able to recognize one specific image or images of dogs that you have defined in advance, either of these should be ok. You might have to manipulate your dog images to get good features they can identify and track. Natural objects can be problematic.
General object recognition (being able to recognize a picture of any dog, not known beforehand) is still a research topic. There are approaches, but they're mostly very computationally intensive, and most mobile solutions involve offloading the serious computation to a server. Recognition of simple outline sketches however is more tractable, there's a great paper called "Shape recognition and pose estimation for mobile augmented reality" (I can't find a copy online, but the IEEE link is here) that uses contours to identify objects - this is light enough to run on a mobile (and it's pure genius).