Polynomial Moving Fitting Method for Edge Identification

2011 ◽  
Vol 308-310 ◽  
pp. 2560-2564 ◽  
Author(s):  
Xiang Rong Yuan
Keyword(s):  
Edge Detection ◽  
Curve Fitting ◽  
Polynomial Function ◽  
High Order ◽  
Polynomial Fitting ◽  
Fitting Method ◽  
Order Polynomial ◽  
Better Than ◽  
Low Order

A moving fitting method for edge detection is proposed in this work. Polynomial function is used for the curve fitting of the column of pixels near the edge. Proposed method is compared with polynomial fitting method without sub-segment. The comparison shows that even with low order polynomial, the effects of moving fitting are significantly better than that with high order polynomial fitting without sub-segment.

scholarly journals High-Order Polynomial Fitting Assistance for Fast Double-Peak Finding in Brillouin-Distributed Sensing

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 187
Author(s):  
Marcelo A. Soto ◽  
Alin Jderu ◽  
Dorel Dorobantu ◽  
Marius Enachescu ◽  
Dominik Ziegler
Keyword(s):  
Optical Fibers ◽  
High Order ◽  
Polynomial Fitting ◽  
Gaussian Fitting ◽  
Peak Finding ◽  
Fitting Method ◽  
Fold Reduction ◽  
Order Polynomial ◽  
Fitting In ◽  
Distributed Brillouin Sensor

A high-order polynomial fitting method is proposed to accelerate the computation of double-Gaussian fitting in the retrieval of the Brillouin frequency shifts (BFS) in optical fibers showing two local Brillouin peaks. The method is experimentally validated in a distributed Brillouin sensor under different signal-to noise ratios and realistic spectral scenarios. Results verify that a sixth-order polynomial fitting can provide a reliable initial estimation of the dual local BFS values, which can be subsequently used as initial parameters of a nonlinear double-Gaussian fitting. The method demonstrates a 4.9-fold reduction in the number of iterations required by double-Gaussian fitting and a 3.4-fold improvement in processing time.

2-Dimension Polynomial Fitting for the Edge Detection

2013 ◽  
Vol 389 ◽  
pp. 969-973
Author(s):  
Xiang Rong Yuan
Keyword(s):  
Edge Detection ◽  
Polynomial Function ◽  
One Dimension ◽  
Grey Level ◽  
Polynomial Fitting ◽  
Two Dimension ◽  
Level Data ◽  
Dimension Polynomial ◽  
The One ◽  
Better Than

The gray-scale digital image is two-dimension, most of the previous polynomial fitting methods for edge detection belong to one-dimension methods. The new method of two-dimension polynomial fitting for edge detection is presented. The grey level data of the interest area around the edge in the image are fitted by the two-dimension polynomial function. The edge of interest is identified by finding the maximum of the form of gradient of the fitting function. Because the two-dimension fitting is actually more suitable for the two-dimension image, the fitting results of two dimension method are significantly better than that of the one-dimension method. It is shown through the analysis of the synthesis image that the results of surface fitting and edge identification used of the proposed method are quite good.

Grasshopper [Chondracris rosea rosea (De Geer)] Incisors Cutting Edge Contour Data Extraction and Quantitative Analysis

2013 ◽  
Vol 461 ◽  
pp. 144-151
Author(s):  
Chang Ying Li ◽  
Hong Lei Jia ◽  
Zhi Hong Zhang ◽  
Gang Wang ◽  
Hong Chang Wang
Keyword(s):  
Point Cloud ◽  
Polynomial Function ◽  
Data Extraction ◽  
Outer Edge ◽  
Outer Margin ◽  
Cutting Edge ◽  
Geometrical Structures ◽  
Detection Technology ◽  
Fitting Method ◽  
Order Polynomial

Grasshopper [Chondracris rosea rosea (De Geer)] possesses sharp and serrated incisors that have an advantageous capacity for cutting crops including leaves and stalks. To quantitatively analyze the geometrical structures of the incisors cutting edge, MATLAB digital image processing and edge detection technology were used to obtain incisors outer margin 2-dimensional point cloud from incisors stereomicroscope photograph. Then, the least squares fitting method was used to fit the curves mathematical model and the outer margin curves of incisors which were segmented into five curves. The serrated outline of incisor was fitted and expressed by nine-order polynomial function. Furthermore, the second derivative and curvature of the outer edge curves were calculated. Finally, the geometrical characteristics of grasshopper incisors outer edge curves were analyzed and discussed. In conclusion, the special shaped incisor of grasshopper is a potential prototype that can be exploited to develop new cutting element to cut lignocellulosic biomass more efficiently. These results would be helpful for designing cutting elements on crop harvesting, biomass size reduction and other cutting machinery.

scholarly journals Calculation of Coefficients of Cassegrain Telescope Mirrors

2011 ◽  
Vol 8 (1) ◽  
pp. 161-167
Author(s):  
Baghdad Science Journal
Keyword(s):  
Optical System ◽  
Curve Fitting ◽  
Polynomial Function ◽  
Rayleigh Criterion ◽  
Fitting Method ◽  
Least Squares Curve Fitting ◽  
Telescope Mirrors ◽  
Cassegrain Telescope ◽  
Curve Fitting Method ◽  
Rayleigh Limit

In the present work, a program for calculating the coefficients of the Aplanatic Cassegrain Telescope (ACT) system, free from the effects of spherical and coma aberrations, were constructed. In addition, the two-mirrors of the optical system, as aspherical surfaces, were adopted. This means, that the two-equations of the mirrors are assumed to be polynomial function of five even terms only. The numerical method, least-squares curve fitting method to calculate the two-mirror coefficients system, was adopted. For choosing the values and ratios that give the best results, Rayleigh Criterion (Rayleigh Limit), for purpose of comparison and preference, was adopted.

scholarly journals A high order derivation method for distribution network transient data

2021 ◽  
Vol 243 ◽  
pp. 01004
Author(s):  
Bo Xiao ◽  
Li Lv ◽  
Yuxuan Kang ◽  
Qingyu Xie ◽  
Xinyang Wang
Keyword(s):  
Distribution Network ◽  
Least Square Method ◽  
Distribution Networks ◽  
High Order ◽  
Least Square ◽  
Polynomial Fitting ◽  
Base Function ◽  
High Order Derivative ◽  
Order Derivation ◽  
Low Order

Nowadays, high-order data needs to be processed quickly and accurately by various algorithms in distribution networks. It is difficult to ensure the accuracy of calculation both in low-order and high-order cases, due to the theoretical limitations of traditional high-order derivation methods. Aimed to improve the calculation accuracy, a new high-order derivative method based on the polynomial fitting is proposed in this paper. By analyzing the transient characteristics of voltage and current signals in the distribution network, the base fitting-function can be selected, and the coefficient of the base function can be obtained to fit the objective function by the least square method. The original discrete data will be replaced by new fitting-function for derivative operation, which not only ensures the anti-interference ability, but also overcomes the limitations of the traditional polynomial fitting method in high-order cases. The simulation results show that this method has high accuracy in high-order and low-order cases, and has good accuracy and anti-interference ability.

Study on Static Deformation Characteristics of Mental Rubber Material

2010 ◽  
Vol 97-101 ◽  
pp. 826-829
Author(s):  
Dong Wei Li ◽  
Zhong Bo He ◽  
Guo Quan Ren ◽  
Lei Zhang
Keyword(s):  
Empirical Formula ◽  
High Order ◽  
Static Deformation ◽  
Deformation Characteristics ◽  
Polynomial Fitting ◽  
Rubber Material ◽  
Damping Material ◽  
Order Polynomial ◽  
Rubber Component

Mental rubber material is a new kind of high elastic and large damping material. In this paper the static deformation of mental rubber components had been studied from stretch, compression and shearing experiment. By the method of high-order polynomial fitting, the empirical formula of static deformation characters of mental rubber component had been established, and some deformation rules of mental rubber had been obtained.

Optimization of inscribed hexagonal fractal slotted microstrip antenna using modified lightning attachment procedure optimization

2020 ◽  
Vol 12 (6) ◽  
pp. 519-530
Author(s):  
Rohit Anand ◽  
Paras Chawla
Keyword(s):  
Curve Fitting ◽  
Patch Antenna ◽  
Microstrip Antenna ◽  
Optimization Technique ◽  
Research Work ◽  
Geometrical Parameters ◽  
Fractal Antenna ◽  
Fitting Method ◽  
Curve Fitting Method ◽  
Better Than

AbstractAn inscribed hexagonal fractal slotted patch antenna with some additional geometry and slots is proposed for the optimization in this paper. This research work is concerned with the optimization of this slotted fractal antenna with the help of the curve-fitting method in conjunction with the modified version of Lightning Attachment Procedure Optimization (MLAPO) technique. The data required for the curve-fitting technique and for the optimization technique have been obtained by varying some of the parameters of the proposed antenna. Different equations are developed to know the relations between these parameters of the proposed antenna. The MLAPO technique is applied thereafter to calculate the different optimized geometrical parameters to optimize the bandwidth for the proposed antenna. The optimized geometrical parameters are verified with the help of a parametric variation to justify the reliable optimization. The bandwidth obtained by the MLAPO technique has been found to be better than that obtained by PSO and normal LAPO algorithm. The prototype of the optimized antenna is fabricated and the experimental results are found to be compatible with the results obtained by simulation. The proposed optimized antenna may be utilized in various applications in C and X bands.

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