10 Normalization
About1 Introduction2 Image Recognition3 TransApplet4 API5 Interface6 Input7 Image Display8 Preprocessing9 Processing10 Normalization11 Parameter Class12 Image Signatures13 Unsupervised Filters14 BioFilters15 NeuralFilters16 Dynamic Library17 NeuralNet Filter18 Parameters19 Input Options20 Database Input21 Video Input22  Live Video Input23  Counting & Tracking24  Counting 25  Batch Job26 ImageFinder for DOS27 ImageHunt 28 Support Packages

10.1 Class Name 
10.2 Class Overview 
10.3 Link to Class 
10.4 Parameters 
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10.   Normalization

This chapter introduces a filter, Reduction Filter. From the userís and programmerís point of view, it means the setting of several parameters. This filter, together with the Image PreProcessing Filter and Image Processing Filters, will be passed to later layers as parameters.

If you are not interested in the details, you can skip this chapter.

The Normalization sub-layer will prepare the images for the underlying NeuralNet filters. The neural net deployed in the ImageFinder, by default, is a 100x100 array of neurons. While any size of ABM neural net can be used, when coming to a particular application, a decision has to be made. The ImageFinder uses 6 different sizes:

  •    10,000 neurons,
  •    8,100 neurons,
  •    6,400 neurons,
  •    4,900 neurons, or
  •    2,500 neurons.


[Home][About][1 Introduction][2 Image Recognition][3 TransApplet][4 API][5 Interface][6 Input][7 Image Display][8 Preprocessing][9 Processing][10 Normalization][11 Parameter Class][12 Image Signatures][13 Unsupervised Filters][14 BioFilters][15 NeuralFilters][16 Dynamic Library][17 NeuralNet Filter][18 Parameters][19 Input Options][20 Database Input][21 Video Input][22 Live Video Input][23 Counting & Tracking][24 Counting ][25 Batch Job][26 ImageFinder for DOS][27 ImageHunt ][28 Support Packages]

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