Approximating offset Curves using Bezier curves with high accuracy

Rababah, Abedallah; Jaradat, Moath

doi:10.11591/ijece.v10i2.pp1648-1654

Cited by 3 publications

(4 citation statements)

References 22 publications

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“…Note that the points p 1 (p 5 ) and p 2 (p 4 ) in both branches are very close to each other and can not be distinguished from each other. The results in this paper can be used to improve the results obtained in [16][17][18][19][20][21][22][23] see also the results in [24,25].…”

Section: Resultssupporting

confidence: 53%

The best sextic approximation of hyperbola with order twelve

Rababah¹,

Rababah²

2020

IJECE

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In this article, the best uniform approximation for the hyperbola of degree 6 that has approximation order 12 is found. The associated error function vanishes 12 times and equioscillates 13 times. For an arc of the hyperbola, the error is bounded by 2:4 x 10-4. We explain the details of the derivation and show how to apply the method. The method is simple and this encourages and motivates people working in CG and CAD to apply it in their works.

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Section: Resultssupporting

confidence: 53%

The best sextic approximation of hyperbola with order twelve

Rababah¹,

Rababah²

2020

IJECE

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“…The obtained MSE value by the bezier curve, in general, is classified as the least. This is suited to Rababah and Jaradat stating that the cubic bezier curve can minimize the error and be more accurate than the approximation method [16]. Okumura states the cubic bezier curve has good performance in representing geometric shapes [15].…”

Section: The Equation Of Cubic Bezier Curve Formentioning

confidence: 99%

“…The cubic bezier curve is a flexible curve that follows the altering track [19]- [21]. Cubic bezier curve builds curves smoothly [22], more accurately than other approximation methods [15], [16]. The cubic bezier curve has four control values that could drive the curve.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Bond Yield Curve Using Cubic Bezier Curve

Siswanah

2022

BAREKENG: J. Math. & App.

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Investors attracted to Bond have to analyze the Bond yield curve. In this study, the bond yield curve is modeled using a cubic bezier curve. The cubic bezier curve is flexible, precise, and simple to use and evaluate. The bonds used in this study are Surat Berharga Negara (Government Paper) Fix Rate type dated August, 2nd–6th 2021. Bond data is obtained from the Indonesia Stock Exchange https://www.idx.co.id. The results show that the bond yield curve that is formed varies because bond yields change every time following market developments. The cubic bezier curve is able to model the bond yield curve well. Cubic bezier curves have 4 control values that help guide the curve well. The MSE value obtained by the bezier curve is small in general. The MSE values of the cubic bezier curve for the Bond yield data, sequentially from the least to the greatest, are 0,098 on August 4th, 2021; 0,1719 on August 5th, 2021; 0,2161 on August 3rd, 2021; 0,2498 on August 6th, 2021; and 0,2906 on August 2nd, 2021.

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“…After correctly pairing, the fitting connection of the pairs appears simple. This paper uses the Bezier curve (Rababah & Jaradat, 2020) to perform the fitting.…”

Section: Fitting Connectionmentioning

confidence: 99%

Tooth identification based on teeth structure feature

Wang

Mao

et al. 2020

Systems Science & Control Engineering

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Massive disasters, like earthquake and fire, can easily damage most features of the human body, which bring difficulties in cadaver identification. In this paper, to improve the efficiency and accuracy of forensic autopsy, a novel tooth identification strategy based on teeth structure features from dental impression images is proposed. The strategy achieves identification including tooth mark segmentation, teeth structure feature extraction, and matching. To resolve the problem of too much noise, we propose a locating segmentation method based on object detection to segment every single tooth mark contour. Finally, to evaluate the proposed strategy more objectively, we propose an indicator named rate of filtration based on the indicator accuracy. The experimental results show that using only upper-jaw teeth, our method achieves a rate of filtration of 90.45% for 47 persons comprised of 311 images, and an accuracy of 86.17% for top-5 (top 12%) image matching, which are highly encouraging. To the best of our knowledge, the proposed method is the first to use dental impression images to achieve tooth identification.

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Approximating offset Curves using Bezier curves with high accuracy

Cited by 3 publications

References 22 publications

The best sextic approximation of hyperbola with order twelve

The best sextic approximation of hyperbola with order twelve

Modeling of Bond Yield Curve Using Cubic Bezier Curve

Tooth identification based on teeth structure feature

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