I'm trying to detect the class & location of handwritten alphanumerics in a given image,
after looking around I found that the best way to achieve that is using deep neural networks, is there is a way to achieve that using tensorflow? (I would like to come up with something fast as it will be used in a live detection app on Android & IOS). more importantly, what kind of dataset can I use for this? will EMNIST be good for that?
or can I use YOLOV2 but with Alphanumerics for that ? if that's possible can EMNIST be used?
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Google goggles is the latest android application designed to search stuffs on the internet by PHOTO.
Now one can upload photo to application and then it will find related profiles and other links on the internet.
I want to know that which mechanism they are using behind that ?
Firstly, I think about color intensity but it might not work..then I think about shape distribution to x axis and y axis with color intensity but i think its not correct.
Now can anyone tell me that which technology they are using in back end ?
Now can anyone tell me that which technology they are using in back
end ?
There are some possibilities. They maybe use neural network like rofls says but I think they are using Data Mining with genetic algorithm I think the method is more effective for searching and clustering with very big data. Here a very good explanation of data mining using genetic algorithm and another paper about it Incremental Clustering in Data Mining
Yes, they are using the Machine Learning. Most likely something like Neural Networks, where there is essentially "black box" that predicts the correct thing. See this: Where to start Handwritten Recognition using Neural Network?, for an example. They train there neural networks on huge servers though, which is why they can deal with complicated images, etc... unlike our computers would be able to.
I would like to know if it is possible to register a movement close to the camera, and then perform some actions inside an app.
This was possible on Symbian, so it should be also on newer Android-powered phones. The problem is I can't find any resource to get started with.
Does anybody have any ideas on where I should start?
Looks like there's a library created over on Google Code: http://code.google.com/p/android-motion-detection/
If you want something a little more powerful, you can also run OpenCV on Android: http://opencv.org/android Don't think you will be able to do anything detecting the distance without another camera or a different type of sensor (like sonar) though.
As a bonus, depending on what your are trying to achieve, there's even a nice API doesn't involve anything additional to the Android SDK: http://developer.android.com/reference/android/media/FaceDetector.Face.html
I am developing a currency identification system for blind people. I need to check if the full currency note has been captured so I used square detection for that. It is currently working when the background is pure black or white, but not when the background is more advanced. What techniques can I use to solve this problem?
I am using OpenCV as my image processing framework. Can I use convolution? How?
need enhancement for square detection.
Result image of my code:
I am not sure whether rectangle detection is the best solution for what you want to do.
It will only work efficiently if the picture is taken right up from the money, and as you say will not be robust to cluttered backgrounds.
Is there a precise reason for not going to a direct pattern recognition system ?
I'd start with a picture of my currency and try to perform object recognition with it.
You will find loads of tutorials that can help you on the web, like for bottles or for bowls.
You might have a lot of possibilities, due to the number of currencies but you know it to be a finite number at least.
Say I have a set of say 100 stored images (say sports team logos, rather than very similar images like faces) in my android app. In a manner similar to google goggle's continuous mode, I would like to use the camera to decide which image is being focused on.
What is the best, most efficient way to accomplish this? Any open source libraries, sdks etc would be great.
Thanks.
If you would like serverside recognition you should check out kooaba's API. its free for small reference databases such as yours and the best in the field...
Www.kooaba.com
I would like to develop or use an existing platform that will allow me to view custom vector data and use it as a map on mobile phones such as Android/IPhone (Maybe even WP7).
I'm hoping that there's already a good infrastructure for what I need so I would not need to develop a whole infrastructure by myself.
In Conclusion -
Is there any existing platform that may answer my needs?
If not, how would you guys suggest I should begin? How should I save my vector data? How could I read it? Should I view it with a graphics engine like OpenGL? Is there any chance this solution could be cross-platform?
I know that it's possible since it was already done with apps like Waze. And it works the same on iOS and Android.
Thanks!
After much research I found a solution that fits most of my needs.
At the moment I decided to go on Android only so I'm using AndEngine (In the future I guess it would be pure OpenGL).
AndEngine can read .svg files and turn them into PNGs at runtime, and also has a built in support for ZoomCamera which allows me to pan and zoom the map very easily.
I'm converting the SVG to PNG because apparently mobile devices do not have a very good anti-aliasing support, and rendering curved paths can also be a problem.