Automatic G1 Surface Reconstruction from Serial Cross-Sectional Images

Yahya, Fatimah; Ali, Jamaludin Md; Majid, Ahmad Abd.; Ibrahim, Arsmah

doi:10.1007/978-3-540-85891-1_12

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…There are a lot of studies in reconstruction of 2D images especially font and character images. Non-Roman character digitization such as Chinese [6,7] and Arabic [8,9] are the common application of 2D images curve fitting that are most researcher prefer to do on their research. According to [10], this type of character known as cursive, complex and needs more attentions.…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Shape Parameters of Beta-Spline Using Particle Swarm Optimization

Suliman

Afrouzi²

2018

IJET

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Beta-spline is an alternative curve for 2D font representation. It is preferred since it has G2 continuity and two shape parameters, that can be used to control the curve shape. These shape parameters can also be used to optimize the error between fitted curve and original data points. Commonly, most of the researcher use value of shape parameters of beta-spline as and or some of the researcher choose any random value of these two shape parameters that suitable to be used in beta-spline curve fitting. The values of shape parameters are very important since the values affect the total error of the fitted curves. Thus, in this paper, Particle Swarm Optimization (PSO) is employed to determine the optimum value of the two shape parameters that will optimize the approximation error of the fitted curve. The technique is applied on two fonts: ى and δ, and tested using various number of iterations and populations.

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