Object Discernment by “A Difference Which Makes a Difference”
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Gregory Bateson is well known for defining information by stating “In fact what we mean by information – the elementary unit of information – is a difference which makes a difference…” This conceptual perspective has the merit of simplicity and generality. Simplicity, in addressing the complexity of information. Generality, in seeking applicability to any and every field of human experience. The purpose of this paper is to focus the applicability of this conceptual approach by Bateson and use it to perform a calculation of taking the difference between two grey-level digital images that are shifted one relative to the other. The digital images take the place of the field of view that a human being would have access through her sense of vision at two different spatial/temporal instances. The results show that it is possible to highlight the edges of the objects under scrutiny, as well as to highlight other differences within the object. Bateson’s “difference that makes a difference” would seem to provide a first step in the elusive meaning making process of humans.
KeywordsGregory Bateson Difference Idea Edge detection Digital image Image processing
The authors would like to acknowledge the reviewers for their comments and suggestions, which have helped to significantly improve the content of this paper.
Compliance with ethical standards
Conflict of Interest
The authors declare that they have no conflict of interest.
- Bateson, G. (1972). Steps to an ecology of mind. Northvale: Jason Aronson Inc..Google Scholar
- Gibson, J. J. (1986). The ecological approach to visual perception. New York: Psychology Press.Google Scholar
- Gonzalez, R. C., & Woods, R. E. (2008). Digital image processing (3rd ed.). Upper Saddle River: Prentice Hall.Google Scholar
- Gonzalez, R. C., Woods, R. E., & Eddins, S. L. (2009). Digital image processing using MATLAB (2nd ed.). S.I.: Gatesmark Pub.Google Scholar
- Hoffmeyer, J., & Emmeche, C. (1991). Code-duality and the semiotics of nature. In M. Anderson & F. Merrell (Eds.), On semiotic modeling (pp. 117–166). Berlin and New York: Mouton de Gruyter.Google Scholar
- Jähne, B. (2005). Digital image processing (6th ed.). Berlin: Springer-Verlag.Google Scholar
- Meister, M., & Berry, M. J., II (1999). The neural code of the retina. Neuron, 22(3), 435–450, https://doi.org/10.1016/S0896-6273(00)80700-X.
- Nixon, M. S., & Aguado, A. S. (2002). Feature extraction and image processing. Woburn: Newnes.Google Scholar
- Pratt, W. K. (2007). Digital image processing: PIKS Scientific inside (4th ed.). Hoboken: Wiley-Interscience.Google Scholar
- Ratliff, F. (1965). Mach bands: Quantitative studies on neural networks in the retina. San Francisco: Holden-Day.Google Scholar