14.6 Stamp
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14.1 Parameters 
14.2 United Way 
14.3 Tabasco 
14.4 Mr. Potato 
14.5 Monopoly 
14.6 Stamp 
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14.6   Stamp – Translation Symmetry

The images used in this section are in the directory “.\ex_stamp\”. In this section, we try to identify 2 stamps. Rather than use an existing image to search, we will focus on building a sample image for matching.

14.6.1   Example 1

The first example retrieves images like the following:

We will build a sample image as follows:

There are two ways to run this example:

  •    Batch
  •    Manual

The Batch Run takes only two clicks:

  • Click “Examples/Neural Net/Stamp 1 - T” ;
  • Click “Batch/Run”.

The Manual Run requires a few more clicks:

Input:

    Training:    .\ex_stamp\class1.jpg

    Search:      .\ex_stamp\

Parameters

    Edge Filter:          (Image Processing---------------1st box)

      None

    Threshold Filter:   (Image Processing---------------2nd box)

       Default

    Clean Up Filter:    (Image Processing---------------3rd box)

       None

    NeuralNet Filter Parameters:   (Neural Net Parameters)

      Translation Symmetry

      Blurring = 8

      Sensitivity = 45

      InternalCut = 40 %

Operation

  • Click the "Key Segment" button and select ".\ex_stamp\class 1.jpg";
  • Click the "Source" button and select ".\ex_stamp\";
  • Set the Parameters as specified above;
  • Click the "Neural Net\Train" button to train the filter;
  • Click the "NeuralNet\matching\1:N (key vs Source)" button to make a search.

Results

 

ID                     Name                       Path                        Score            X   Y     W   H

CLASS1        CLASS1.JPG          C:\...\ex_stamp\    128000000   36  24  244 272

CLASS1_1    CLASS1_1.JPG    C:\...\ex_stamp\    39680             64  24  244 272

class1_10       class1_10.jpg        C:\...\ex_stamp\    18112             12  28  244 272

CLASS1_2    CLASS1_2.JPG    C:\...\ex_stamp\    44160             44  20  244 272

CLASS1_3    CLASS1_3.JPG    C:\...\ex_stamp\    19584              4   24  244 272

CLASS1_4    CLASS1_4.JPG    C:\...\ex_stamp\    45120            68  24  244 272

CLASS1_5    CLASS1_5.JPG    C:\...\ex_stamp\    53312            36  24  244 272

CLASS1_6    CLASS1_6.JPG    C:\...\ex_stamp\    43136            68  36  244 272

CLASS1_7    CLASS1_7.JPG    C:\...\ex_stamp\    40960            56  52  244 272

CLASS1_8    CLASS1_8.JPG    C:\...\ex_stamp\    43648            44  44  244 272

CLASS1_9    CLASS1_9.JPG    C:\...\ex_stamp\    28544             88  24  244 272

Summary

# Images        = 104

    # To be retrieved   = 11

    # Retrieved Correctly   = 11

    # Missed        = 0

    Hit Ratio       = 100%

 

14.6.2   Example 2

The second example retrieves images like the following:

We will build a sample image as follows:

There are two ways to run this example:

  •    Batch
  •    Manual

 

The Batch Run takes only two clicks:

  • Click “Examples/Neural Net/Stamp 2 - T” ;
  • Click “Batch/Run”.

The Manual Run requires a few more clicks:

Input:

     Training:     .\ex_stamp\class7.jpg

    Search:        .\ex_stamp\

Parameters

    Edge Filter:             (Image Processing---------------1st box)

      None

    Threshold Filter:      (Image Processing---------------2nd box)

      Default

    Clean Up Filter:      (Image Processing---------------3rd box)

       None

    NeuralNet Filter Parameters:    (Neural Net Parameters)

      Translation Symmetry

      Blurring = 12

      Sensitivity = 40

      InternalCut = 70

Operation

  • Click the "Key Segment" button and select ".\ex_stamp\class 7.jpg";
  • Click the "Source" button and select ".\ex_stamp\";
  • Set the Parameters as specified above;
  • Click the "Neural Net\Train" button to train the filter;
  • Click the "NeuralNet\matching\1:N (key vs Source)" button to make a search.

Results

ID                    Name                         Path                          Score                X     Y   W      H

CLASS7        CLASS7.JPG          C:\...\ex_stamp\        128000000      36  24  272   256

CLASS7_1    CLASS7_1.JPG     C:\...\ex_stamp\         61184             36  24  272    256

class7_10       class7_10.jpg          C:\...\ex_stamp\        29504             48  36  272    256

CLASS7_2    CLASS7_2.JPG      C:\...\ex_stamp\        26240             56  28  272    256

CLASS7_3    CLASS7_3.JPG      C:\...\ex_stamp\        22336             40  52  272    256

CLASS7_4    CLASS7_4.JPG      C:\...\ex_stamp\        26880             56  28  272    256

CLASS7_5    CLASS7_5.JPG      C:\...\ex_stamp\        21184             52  32  272    256

CLASS7_6    CLASS7_6.JPG      C:\...\ex_stamp\        21568             56  32  272    256

CLASS7_7    CLASS7_7.JPG      C:\...\ex_stamp\       50688              72  4   272     256

CLASS7_8    CLASS7_8.JPG      C:\...\ex_stamp\       33536              28  0   272     256

CLASS7_9    CLASS7_9.JPG      C:\...\ex_stamp\       44096              48  0   272     256

Summary

    # Images        = 104

    # To be retrieved   = 11

    # Retrieved Correctly   = 11

    # Missed        = 0

    Hit Ratio       = 100%

 

[Home][About][1. Introduction][2. Overview][3. GUI][4. Image Signatures][5. Unsupervised Filters][6. Results & Analysis][7. BioFilters][8. NeuralFilters][9. Duplicated Documents][10. Face Recognition][11. Auto Part Recognition][12. Dynamic Library][13. NeuralNet Filter][14. Segment Variation][15. TV Advertisements][16. Counting & Tracking][17. Image PreProcessing][18. Image Processing][19. Batch Job][20. Parameters][21. Input Option][22. Application Developers][23. Reference Manual][24. Support Services][25. Readme.txt]

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