A Novel Method of 2D Computation and Reconstruction

D. Jakóbczak
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引用次数: 0

Abstract

Proposed method, called Probabilistic Nodes Combination (PNC), is the method of 2D curve modeling and handwriting identification by 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 need 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.
一种新的二维计算与重建方法
本文提出的方法称为概率节点组合(Probabilistic Nodes Combination, PNC),是一种利用关键点集进行二维曲线建模和手写识别的方法。将节点作为签名或笔迹的特征点进行建模和识别。手写字母或符号的识别需要建模,通过选择概率分布函数和节点组合来建立每个单个符号或字符的模型。通过节点组合和参数γ作为概率分布函数进行PNC建模,可以对每个特定字母或符号进行曲线参数化和插值。二维曲线通过节点组合和不同函数作为连续概率分布函数进行建模和插值:多项式、正弦、余弦、正切、余切、对数、指数、弧sin、弧cos、弧tan、弧cot或幂函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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