A Probabilistic Neural Network-Based Module for Recognition of Objects from their 3-D Images

2. Basic Requirements For 3-D Object Recognition

Before proceeding with the description of the details of the proposed module, a discussion of the basic requirements of any object recognition module is presented. An object recognition module should possess the following main characteristics (other attributes can also be important dependent on the particular problem at hand and the type of measured signals to recognize the objects):

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  Invariance to rotation: If the module is presented with an image taken at a slightly different angle, it should still be able to recognize the object correctly;

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  Invariance to translation: If the module is presented with a slightly translated image (i.e. there is a shift in the position of the object), it should still be able to recognize the object correctly;

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  Invariance to slight deformation: To illustrate this point, the example of mine recognition is considered. A mine recognition module is liable to be trained on old images of mines. If these mines that are to be recognized have been buried several years ago, they will be probably hampered by inevitable deformations. The recognition module should be able to cope with this.

3. The Proposed Object Recognition Module

The previous arguments about recognition modules basic requirements motivated the proposal of the object recognition module that is to be detailed in this section.