Geometric modeling and applications of generalized blended trigonometric Bézier curves with shape parameters

A Bézier model with shape parameters is one of the momentous research topics in geometric modeling and computer-aided geometric design. In this study, a new recursive formula in explicit expression is constructed that produces the generalized blended trigonometric Bernstein (or GBT-Bernstein, for short) polynomial functions of degreem. Using these basis functions, generalized blended trigonometric Bézier (or GBT-Bézier, for short) curves with two shape parameters are also constructed, and their geometric features and applications to curve modeling are discussed. The newly created curves share all geometric properties of Bézier curves except the shape modification property, which is superior to the classical Bézier. The C3 and G2 continuity conditions of two pieces of GBT-Bézier curves are also part of this study. Moreover, in contrast with Bézier curves, our generalization gives more shape adjustability in curve designing. Several examples are presented to show that the proposed method has high applied values in geometric modeling.


Introduction
Bézier curves are the powerful mechanism for modeling in computer-aided geometric design (CAGD) and computer graphics (CG). Bézier curves have a lot of applications in the areas of science, engineering, and technology such as: railway route or highway modeling, networks, animation, computer-aided design system, robotics, environment design, communications, and many other fields due to their computational simplicity and stability. However, the classical Bézier curves have still some noiseless limitations due to their fixed shape and position relative to their control polygon [1][2][3]. In geometric modeling and engineering, practical applications of Bézier curves are restricted due to their shortcomings, and to overcome these shortcomings, a lot of work has been carried out [4][5][6][7][8][9][10]. The control over the shape and position of curves is enhanced by introducing the shape control parameters into Bézier approach. Another limitation in the classical Bézier curves is their representation in a polynomial form. Thus many scholars try to search for the solution of this issue in a non-polynomial function space.
Over the past few years, a significant work has been carried out, with the help of trigonometric functions, polynomials, or their combination, for the description of curves and surfaces. These trigonometric polynomials play a significant role in many fields like medicine, electronics [11], and computer-aided geometric design [12]. In recent years, geometric modeling by using trigonometric polynomials has achieved much consideration. Yan and Liang [13] constructed Bézier-like curve and rectangular Bézier-like surface based on a new type of polynomial basis functions with single shape parameter which they achieved by the recursive technique. Hu et al. [14] constructed geometric continuity conditions for the construction of free-form generalized Bézier curves with n shape parameters. These free-form complex shape-adjustable generalized Bézier curves can be modeled by using shape-adjustable generalized Bernstein basis functions. These newly proposed approaches not only take over the benefits of classical Bézier curve and surface schemes, but also resolve the issue of shape adjustability of Bézier curves and surfaces with the help of multiple shape parameters. In 2019, BiBi et al. [15] proposed a new approach using the generalized hybrid trigonometric Bézier curve (shortly, GHT-Bézier) with shape parameters to solve the problem in construction of some symmetric curves and surfaces. These curves are easily modified by changing the values of shape parameters. Using GHT-Bézier curves, they constructed some free-form complex curves with restriction of parametric continuity. To show the efficiency of modeling, the authors also constructed different types of symmetric curves and surfaces with their continuity conditions and symmetric formulas. Maqsood et al. [16] constructed the generalized trigonometric Bézier (GT-Bézier) curves via GT-basis functions with shape parameters. They modeled some complex curves and surfaces using C 3 and G 2 continuity conditions. The proposed basis functions provide an alternative approach to generate the complex curves using C 3 and G 2 continuity conditions with simple and straightforward calculation for proposed algorithm because they are blended with linear polynomials rather than trigonometric functions.
In 2004, the cubic trigonometric polynomial curves were constructed by Han [17] with a shape parameter and C 2 and G 3 continuity conditions having nonuniform knot vector. It has been observed that the trigonometric polynomial curves can better approximate to the classical cubic B-spline curves or to the given control polygon than the classical cubic B-spline curves. The cubic trigonometric Bézier basis functions with two shape parameters were developed by Han et al. [18]. They also constructed cubic trigonometric Bézier curve with two shape parameters similar to the classical Bézier curve that was based on these basis functions. They observed that due to the presence of shape parameters the shape of trigonometric Bézier curve better approximates to the given control polygon than the classical cubic Bézier curves. Han and Zhu [19] constructed five trigonometric blending functions using two exponential shape parameters that have geometric properties similar to the classical Bézier curves. The quadratic trigonometric basis functions were constructed by Bashir et al. [20] using two shape parameters. Moreover, they modeled a rational quadratic trigonometric Bézier curve using these trigonometric basis functions as well as two curve segments connected by using C 2 and G 2 continuity conditions. Yan expressed an algebraic-trigonometric mixed piecewise curve with two shape parameters and cubic trigonometric nonuniform B-spline curves with local shape parameters in [21] and [22], respectively. Hu et al. [23] constructed geometric continuity constraints for H-Bézier curve of degree n. Recently, many researchers have developed the positivity-preserving rational quartic spline interpolation [24], cubic triangular patches scattered data interpolation [25], rational bi-cubic Ball image interpolation [26], quasiquintic trigonometric Bézier curve with shape parameters [27], curve modeling by new cubic trigonometric Bézier with shape parameters [28], continuity conditions for G 1 joint of S-λ curves and surfaces [29], generalized Bernstein basis functions for approximation of multi-degree reduction of Bézier curve [30], surface modeling in medical imaging by Ball basis functions [31], and geometric conditions for the generalized H-Bézier model [32] which have many applications in medicine, science, and engineering. Khalid and Lobiyal [33] presented the extension of Lupaş Bézier curves/surfaces and rational Lupaş Bernstein functions with shape parameters having all positive (p, q)-integers values. They presented two techniques named de-Casteljau's algorithm and Korovkin's type approximation based on (p, q)-integers by using two parameter family of Lupaş (p, q)-Bernstein functions. Lupaş [34] studied the q-analogue of the Bernstein operator. Mursaleen et al. [35] presented the analogue of (p, q)-Bernstein operators, which is a generalization of q-Bernstein operators, and studied its approximation properties based on Korovkin's type approximation theorem of (p, q)-Bernstein operators.
In this research work, GBT-Bézier curves with two shape parameters are constructed based on GBT-Bernstein basis functions of degree m. Furthermore, the adjacent GBT-Bézier curve segments are connected using parametric and geometric continuity conditions which can be utilized to model free-form complex shapes. As a continuation of traditional Bézier curves, these GBT-Bézier curves will also offer a new application range in the field of manufacturing industry, computer vision, computer graphics, computer animation, and multimedia technology.
In this work, we make the following technical contributions: • C 3 continuity of the 2D GBT-Bézier curves; • G k (k ≤ 3) geometric continuity of the 2D GBT-Bézier curves. The outline of this paper is structured in the following manner. Some basic definitions and characteristics of GBT-Bézier curves are given in Sect. 2. Continuity constraints for joining the two GBT-Bézier curve segments are discussed in Sect. 3. Some modeling examples are given in Sect. 4. Concluding remarks on this research are given in Sect. 5.

Definition and characteristics of GBT-Bézier curves
The definitions and properties of GBT-Bernstein basis functions and GBT-Bézier curves with shape parameters are given in this section.

GBT-Bernstein basis functions
are called second degree GBT-Bernstein basis functions associated with shape parameters μ, ν. For any integer m (m ≥ 3), the functions, f k,m (z) (k = 0, 1, 2, . . . , m) defined iteratively Remark 1 It is noted that the expressions given in equation (2) differ from the ones we introduced in our earlier work [16] in that we explicitly added polynomial instead of trigonometric functions. We found in our experiments that the trigonometric functions were not intuitive enough for the users to control, while resulting in unnecessarily complex computations. As we prove in this work, we are able to derive sufficiently high order derivative constraints (up to C 3 and G 3 ) while keeping linear polynomial which provided smoother output as compared to Maqsood [16]. We advocate therefore Definition 1 from now on.

Theorem 1 GBT-Bernstein basis functions have the following characteristics:
1. Degeneracy: When μ, ν = 1 and sin( π  Thus, for m = s + 1, according to formula (2), we have Now imagine that the GBT-Bernstein basis functions of degree s are consistent. Then from this inductive hypothesis and iterative formula (2), we have

Convex hull property:
The whole GBT-Bézier curve must be contained inside the control polygon spanned by Q 0 , Q 1 , Q 2 , . . . , Q m . 4. Geometric invariance: The shape of the GBT-Bézier curve is independent of the selection of a coordinate system for the reason that F(z, μ, ν) is an affine combination of the control points, which means it satisfies the next two equations: where Q is a random vector in R 2 or R 3 and M is a random n × n(n = 2, 3, . . . , m) matrix. 5. Variation diminishing property: As GBT-Bernstein basis functions fabricate a class of formalized completely positive basis functions, the GBT-Bézier curves in (13) carry the variation reducing property, which means that a GBT-Bézier curve will have no more intersections with any plane more often than it intersects the correlated control polygon. 6. Shape control property: For a described control polygon, the shape of the traditional Bézier curve can be totally defined by its control points, while the shape of the GBT-Bézier curve can be modified by changing its shape parameters μ, ν although its control polygon remains fixed. From the above expressions, we can conclude that, GBT-Bézier curves interpolate to the terminal points of the control polygon, that is, to the first and the last edge. The abovementioned expressions also show that the value of the first and second derivative at both terminal points on GBT-Bézier curves can be modified by adjusting shape parameters μ, ν, which play a significant role in unwrinkled joining. Figure 2 depicts the influence role of shape parameters μ, ν on quartic and quintic GBT-Bézier curves, that is, if we increase the value of a shape parameter, either μ or ν or both, the GBT-Bézier curve gradually approximates to the control polygon, whereas the points marked on the quartic GBT-Bézier curves correlate to F(0. 2   the values of shape parameters μ, ν and also exhibits the graphs of 2nd, 3rd, 4th, 5th, and 10th degree GBT-Bézier curves. Figure 3(a) shows the graphs of 4th degree GBT-Bézier curves with μ, ν = 1 (purple), 0.5 (blue), 0 (red), -0.5 (black). The first flower presented in Fig. 3(b) is designed by 5th degree GBT-Bézier curves when μ, ν = 1 (purple), 0.3 (red), -0.3 (green), -1 (orange). Figure 3(c) shows the second flower created by 10th degree GBT-Bézier curves with shape parameters μ, ν = 1 (purple), 0.3 (red), -0.3 (green). Figure 3(d) represents a butterfly for multiple values of shape parameters μ, ν = 1 (blue), 0.25 (red), -0.5 (green), which is generated by 2nd and 3rd degree GBT-Bézier curves.

Continuity of GBT-Bézier curves
Practically, the outlook of many products is relatively complicated and cannot be presented by using a single curve. Therefore, contiguous curves are used to design such products. The technique of smooth continuity among curves is used to design complex curves and also a meaningful study in computer-aided design/computer-aided manufacturing (CAD/CAM). Two categories for estimating the continuity of piecewise curves are: • Parametric continuity (C m ), • Geometric continuity (G m ).
The continuity conditions of GBT-Bézier curves in the context of terminal properties of GBT-Bézier curves are given in the following theorem.

Conclusions
In this study, we proposed the GBT-Bézier curves of degree m associated with two shape parameters and studied their characteristics. These proposed GBT-Bézier curves have almost all characteristics of the classical Bézier curves but the shape-adjustable quality is an additional quality if compared to the classical Bézier curves. Moreover, G 2 and C 3 continuity requirements for the construction of composite curves are derived. These special continuity preserving curves have parameters that can control the shape and can be used easily in CAD/CAM. Modeling examples illustrate that the GBT-Bézier curves design can approach the control net closer than the traditional Bézier curves design, and also these designing examples exhibit that the GBT-Bézier curves proposed in this research are simple to apply. In addition this approach gives the degree of freedom of shape and consequently can be utilized to generate a variety of complicated special curves. Moreover, as the newly constructed curves have only two shape parameters, hence the method of shape amendment becomes convenient, and we can anticipate the result after modifying the shape parameter. We believe our work is meaningful and considerable because our proposal supports simplifying the development and computer realization of complicated curves. In the future, we shall generalize these GBT-Bernstein basis functions in quantum and post quantum calculus frame, and they may attract attention of researchers working in approximation theory and CAGD.