Köppen M. & Ruiz-del-Solar J. (1999) Autopoiesis and image processing: Detection of structure and organization in images. In: Mira J. & Sánchez-Andrés J. V. (eds.) International work-conference on artificial neural networks. Springer, Berlin: 442–451.
Köppen M. & Ruiz-del-Solar J.
(
1999)
Autopoiesis and image processing: Detection of structure and organization in images.
In: Mira J. & Sánchez-Andrés J. V. (eds.) International work-conference on artificial neural networks. Springer, Berlin: 442–451.
The theory of Autopoiesis describes what the living systems are and not what they do. Instead of investigating the behavior of systems exhibiting autonomy and the concrete implementation of this autonomy (i.e. the system structure), the study addresses the reason why such behavior is exhibited (i.e. the abstract system organization). This article explores the use of autopoietic concepts in the field of Image Processing. Two different approaches are presented. The first approach assumes that the organization of an image is represented only by its grayvalue distribution. In order to identify autopoietic organization inside an image’s pixel distribution, the steady state Xor-operation is identified as the only valid approach for an autopoietic processing of images. The effect of its application on images is explored and discussed. The second approach makes use of a second space, the A-space, as the autopoietic-processing domain. This allows for the formulation of adaptable recognition tasks. Based on this second approach, the concept of autopoiesis as a tool for the analysis of textures is explored.
Ruiz-del-Solar J. (2000) Computational autopoiesis for texture analysis. In: Suzuki Y., Seppo Ovaska S., Furuhashi T., Roy R. & Dote Y. (eds.) Soft computing in industrial applications. Springer, London: 531–539.
Ruiz-del-Solar J.
(
2000)
Computational autopoiesis for texture analysis.
In: Suzuki Y., Seppo Ovaska S., Furuhashi T., Roy R. & Dote Y. (eds.) Soft computing in industrial applications. Springer, London: 531–539.
The theory of Autopoiesis attempts to give an integrated characterization of the nature of the living systems by capturing the key idea that living systems are systems that self-maintain their organization. This theory makes a complementary definition of the concepts of organization and structure of a system. The organization of a system defines its identity as a unity, while the structure determines only an instance of the system organization. In other words, the organization of a system defines its invariant characteristics. In this article the concept of autopoiesis is explored as a tool to analyze the internal organization of a very special kind of systems, which are the images. More specifically, a computational model of autopoiesis is applied for texture identification through the use of an autopoietic-agent.