Answers.Body: <p>Just use <code>IMGAug</code> library for Applying the 'zoom' augmentation on the images and a convnet (or even MLP) would have no problem in this task. Zooming on the image would be more than enough to use as, as long as your zoom is of sufficient power.</p>
  <p>So apply &quot;zoom&quot; of the same factor on all images, make them bigger, and Convolutional Neural Networks would do fine. Also, If color is not an important feature, then you would be better off rescaling images b/w <code>0</code> and <code>1</code> and making them GrayScale</p>
  
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Answers.CreationDate: 2021-01-08T19:42:43.200Z
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Answers.UserDisplayName: neel g
Answers.Body: <p>Instead of NNs, you can use RANSAC algorithm to calculate homography matrix, but first you need to find feature points. However, if your images are blob-like, you may not get such a successful results. Here some presentations for better understanding: <a href="https://www.cs.umd.edu/class/fall2019/cmsc426-0201/files/17_Homography-estimation.pdf" rel="nofollow noreferrer">cs.umd notes</a> and <a href="http://6.869.csail.mit.edu/fa12/lectures/lecture13ransac/lecture13ransac.pdf" rel="nofollow noreferrer">csail.mit notes</a></p>
  <p>(Also, there might be better image processing tools.)</p>
  
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Answers.CreationDate: 2021-01-07T15:50:05.107Z
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Answers.UserDisplayName: Enes
Body: <p>I have 2 small images. They are basically the same, but differ in rotation and size. I should estimate the parameters for affine transform to get them similar. What network structure can be suitable for this task? For example, those based on convolutional networks did badly, because the pictures are too small.<a href="https://i.sstatic.net/tKQLP.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/tKQLP.png" alt="enter image description here" /></a></p>
  
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Comments.Text: Does it have to be with NNs or do you want to use image processing tools
Comments.UserDisplayName: Enes
Tags: <image-generation>
Title: Can you give me a piece of advise of the network sructure that would be suitable for my task?
UserDisplayName: Colab Colab
ThreadText: # Can you give me a piece of advise of the network sructure that would be suitable for my task?
  
  (Asked by: username_0 on 2021-01-07)
  
  I have 2 small images. They are basically the same, but differ in rotation and size. I should estimate the parameters for affine transform to get them similar. What network structure can be suitable for this task? For example, those based on convolutional networks did badly, because the pictures are too small.[![enter image description here](https://i.sstatic.net/tKQLP.png)](https://i.sstatic.net/tKQLP.png)
  
  **Tags:** image-generation
  > **Comments:**
  > **username_1**: Does it have to be with NNs or do you want to use image processing tools  
  
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  ## 2 answers
  
  ### Answer by username_2 on 2021-01-08. Score: 1
  
  Just use `IMGAug` library for Applying the 'zoom' augmentation on the images and a convnet (or even MLP) would have no problem in this task. Zooming on the image would be more than enough to use as, as long as your zoom is of sufficient power.
  
  So apply "zoom" of the same factor on all images, make them bigger, and Convolutional Neural Networks would do fine. Also, If color is not an important feature, then you would be better off rescaling images b/w `0` and `1` and making them GrayScale
  
  
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  ### Answer by username_1 on 2021-01-07. Score: 1
  
  Instead of NNs, you can use RANSAC algorithm to calculate homography matrix, but first you need to find feature points. However, if your images are blob-like, you may not get such a successful results. Here some presentations for better understanding: [cs.umd notes](https://www.cs.umd.edu/class/fall2019/cmsc426-0201/files/17_Homography-estimation.pdf) and [csail.mit notes](http://6.869.csail.mit.edu/fa12/lectures/lecture13ransac/lecture13ransac.pdf)
  
  (Also, there might be better image processing tools.)
  
  
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