Two-points Interpolation of Curves and Functions


Published: 2023-05-12

Page: 145-156

Dariusz Jacek Jakóbczak *

Department of Electronics and Computer Science, Technical University of Koszalin, Sniadeckich 2, 75-453 Koszalin, Poland.

Krzysztof Rokosz

Department of Electronics and Computer Science, Technical University of Koszalin, Sniadeckich 2, 75-453 Koszalin, Poland.

*Author to whom correspondence should be addressed.


Proposed method, called Probabilistic Nodes Combination (PNC), is the method of 2D functions and curves interpolation and modeling, also handwriting identification with using the set of key points. Nodes are treated as characteristic points of signature or handwriting for modeling and writer recognition. Identification of handwritten letters or symbols requires modeling and the model of each individual symbol or character is built by a choice of probability distribution function and nodes combination. PNC modeling via nodes combination and parameter γ as probability distribution function enables curve parameterization and interpolation for each specific letter or symbol. Two-dimensional curve is modeled and interpolated via nodes combination and different functions as continuous probability distribution functions: polynomial, sine, cosine, tangent, cotangent, logarithm, exponent, arc sin, arc cos, arc tan, arc cot or power function.

Keywords: Handwriting identification, shape modeling, curve interpolation, PNC method, nodes combination, probabilistic modeling

How to Cite

Jakóbczak, D. J., & Rokosz, K. (2023). Two-points Interpolation of Curves and Functions. Asian Journal of Pure and Applied Mathematics, 5(1), 145–156. Retrieved from


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