Understanding the Threshold Process in Harris Corner and Edge Detector I have read the paper Chris Harris , Mike Stephens - A Combined Corner and Edge Detector about the Harris Corner and Edge Detector, but I didn't understand the point that after low and high threshold they have got 5 regions, specially the point where he has got 2 corner classes, can you please explain that to me with image so I can get that point?


here is the part of the paper which I didn't understand:


  
  By applying low and high thresholds, edge hysteresis can be carried out, and this can enhance the continuity of edges.
  
  
  These classifications thus result in a 5-level image comprising:
  



  
    
    Background.
    Two corner classes.
    Two edge classes.
    
  



**Thanks in advance**
After doing the low and high thresholds to the eigenvalues, there will be 2 types of corners:


weak corners which are close to the low thresholding value.
strong corners which are above the high thresholding value.