title: Image Recognition - Binary Descriptor representation in Mat - OpenCV Android
body: <p>I am just curious. I am new here so be please considerate to my somewhat noobish question. </p>
  
  <p>Let's say I am doing  android application with image recognition, where all processes even computationally intensive have to happen on the mobile device cpu. </p>
  
  <p>I am at the stage where I have already processed images  extracted some features from the image. The set of images comes from only one building where it should recognize particular objects of interest (different windows, pictures, artefacts, outside of building). So it's a closed domain and I can provide enough pictures of objects from different angles. I plan to train Neural Network and provide it to app instead of image matching algorithm.</p>
  
  <p>My idea is to extract keypoints, compute descriptors (using FREAK for keypoints ORB for descriptors) and out of those descriptors I would like to end up with single file or array 
  which would end up something like this</p>
  
  <pre><code>    Desc1  Desc2 Desc3 Desc4 DescN......... Class
  _________________________________________________________________________________
  Picture 1     0.121  0.923 0.553 0.22  0.28           "object1" 
  Picture 2     0.22    0.53  0.54 0.55  0.32 .........."object1" (different scale, angle)
  Picture 3     ....    ...    ...   ...  ..   .........."object2"
  Picture N
  Picture N+1
  </code></pre>
  
  <p>so I can give it to neural network for training, however I got stuck as I have no idea how is the binary feature/descriptor represented in the Matrice(Class Mat - openCV). and how would I go on normalising these binary descriptors, so I can feed it to Neural Net(Multi-Layer Perceptron) for training. (even pseudo-code would help greatly)</p>