<p>There are multiple ways in which the problem can be solved. Two approach listed below</p>

<blockquote>
  <ol>
  <li>Using traditional image processing techniques: Do intensity based threshold, Edge detection and others etc. </li>
  <li>use machine learning/ Deep learning:   Please find below reference for  ML/deep learning implementation.</li>
  </ol>
  
  <p><a href="https://arxiv.org/ftp/arxiv/papers/1710/1710.06836.pdf" rel="nofollow noreferrer">https://arxiv.org/ftp/arxiv/papers/1710/1710.06836.pdf</a>
          <a href="https://cse.iitk.ac.in/users/cs365/2015/_submissions/vinsam/report.pdf" rel="nofollow noreferrer">https://cse.iitk.ac.in/users/cs365/2015/_submissions/vinsam/report.pdf</a></p>
</blockquote>

<p>In my opinion/practice Deep learning methods generalize well compared to traditional approach, given lot of training data and compute.</p>
How can i choose a filter or an edge-detection technique that is suitable for a given computer-vision application?
<p>I am trying to build a system to recognize sign language alphabet. I don't have experience working on computer vision because this is my first time. I don't know which filter i should use (sharping , smoothing , sharping then smoothing, smoothing then sharping Or even something else). Not just the filter choice but also other choices like:<br>
1- Image Thresholding methods<br>
2- edge detection techniques<br>
..etc</p>