Possibility-based perception: A reflection on recognizing the pattern of shapes

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Abstract

Within the past years, probability and possibility have both been elaborated as two key concepts in formulating the issue of uncertainty in various domains of decision making like pattern recognition. Possibility pays attention to the existing structure of a pattern (or a situation), while the main concern of probability is to emphasize on the problems experienced in the past. When we talk about "structure" the question is how the meaningful components in a pattern (or a situation) may come into existence based on specific models. Accordingly the perception based on possibility takes us to the paint where a set of possibilities with regard to these meaningful components come together to figure out the class identity of the related pattern based on the possibility of the presence of these specific models.
In this paper, we try to show how the possibility of a pattern class can be assessed on the ground of the information belonging to its meaningful components which are supposed to come into existence based on specific models.
To give a clear image of the proposed approach, recognition of shape patterns that are structural in nature, is taken into consideration.

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References

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History

  • Receive Date: 30 May 2022
  • Revise Date: 14 June 2022
  • Accept Date: 25 June 2022

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