As image pixels are used for computing features, the pixel representation seems to be more general. This has the advantage limitations caused by that bad or missing features can be overcome by a thorough analysis of the pixel space. There is however a price to pay. Consider two face images represented by their pixels. In…
PR System Archives
The Pixel Space
Monday, November 19th, 2012 at
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Pixel Representation
Friday, November 16th, 2012 at
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Good representations enable the recognition of real world objects. They make it possible to compute differences between objects. If the differences between similar objects are always small, they constitute the basis for a generalization. This is the case for a continuous mapping of the original objects, what has been called a compact representation. It may,…
True Representations
Monday, November 12th, 2012 at
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The significance of a proper representation has been discussed here in several ways. The scene is now ready to make a significant step which is not often discussed in the pattern recognition literature. Let us first summarize the observations made so far. Representation is the step in pattern recognition between real world objects or events…
Compactness
Monday, November 5th, 2012 at
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Around 1965 the the concept of compactness was discussed in the Russian pattern recognition literature [1]. It has been almost entirely neglected by the authors of the textbooks published in the West. There is however a strong relation with the careful creation of a good representation as advocated by us. Here we will describe the…
Representation and generalization
Friday, November 2nd, 2012 at
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No two objects in the world are identical. They are all different. Even if they belong to the same class, even if they come from the same production process or when they are twins, they differ. It may take some inspection before we have found the difference. Nevertheless, in spite of the fact that all…
The recognition task
Monday, October 29th, 2012 at
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What do we want to recognize? What are the objects to be classified? What are our examples? What will be our observations? What are the classes we want to distinguish? Are they human defined or are we searching for some truth that might be hidden in the observations but not clearly defined? Many choices to…
Distances and densities
Friday, October 26th, 2012 at
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What is the ground for classifying a new object if we just have some some examples? How to we determine a proper class given a training set? We may find an identical copy in the examples if we are lucky. If there are more identical copies and they belong to different classes we are in…
Features need statistics, as they reduce
Monday, October 22nd, 2012 at
00:00
Is statistics needed for learning? Well, it depends. A definite answer will be postponed for the time being. Here a first step will be made based on the traditional representation used for pattern recognition: the feature space. Objects belonging to different pattern classes differ. Otherwise it would not be possible to distinguish these classes. May…
Statistical pattern recognition
Thursday, September 13th, 2012 at
00:00
Statistical pattern recognition refers to the use of statistics to learn from examples. It means to collect observations, study and digest them in order to infer general rules or concepts that can be applied to new, unseen observations. How should this be done in an automatic way? What tools are needed? Previous discussions on prior…
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