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n 1 = ∑ − S Y i (6) i= 0 If we set accumulator capacity of a unit area value in the accumulator during the more than one area of the value of accumulator generates a pulse, then the number of pulses generated by the demand shall be the total area. digital integration method for circular interpolation To I-quadrant inverse round NR1 explain DDA circular interpolation of the basic principles of law, as shown in Figure 9. Y = n ∑ i= 1 Δy i = − n ∑ i= 1 kx Δt i i (11) IV. SUMMARY This system combined CNC technology and embedded system, designed and implemented the ARM + PLC embedded face cylindrical grinding machine numerical control system hardware&software systems, embedded numerical control system has proven superior performance of the system resources can be configured by software and hardware reduction, access to non-redundant structure, highly-integrated numerical control system.Based on this system face cylindrical grinding machine control system, with versatility, high performance, reliability, system flexibility, cost-effective high advantages, greatly improving the face cylindrical grinding machine automation and efficiency. REFERENCES Figure9. DDA CIRCULAR INTERPOLATION THEORY When the cutting tool along the arc SE , arc radius R, cutting speed of v, the speed of the two axis components of Vx and Vy, fixed point and N (Xi, Yi), based on the similarity relations between triangles can be very : v v v x y = = = K (constant) (7) R Yi X i Where, v = KR; Vx = KY i; Vy = KXi. As the radius R is a constant, if tangential velocity v is uniform, then K is a constant, then the fixed point in two coordinate axis velocity component will vary and change the value of its coordinates. When given a time increment Δ t, the fixed point in X, Y axis displacement increments are as follows: Δ X i = −v X Δt = −KYi Δt (8) Δ Y = v Δt = KX Δt (9) i Y i Due to against the X-axis coordinate values corresponding to a gradual decrease in Quadrant I, so the formula 8, Δ X i expression to take a negative sign, that is, v X and v Y are taking the absolute value. 8 and 9 according to the formula I obtained the first quadrant inverse circular arc DDA Interpolation formula is: X = n ∑ i= 1 Δx i = − n ∑ i= 1 ky Δt i i (10) [1] ZHOU Zude,LONG Yihong,LIU Quan. Embedded-Based network numerical control technology and system [J]. CHINESE JOURNAL OF MECHANICAL ENGINEERING ,2007.43(5):1-6 [2] ShibataT ,YanoM , Kodama F. EmPirical analysis of evolution of Product architecture Fanue numerical controllers from1962 to1997[J]. Research Poliey. 2005. l.34:13-31 [3] WANG Dianhong,LI Weizhong,LIU Bing . Design of Control System Based on ARM Processor [J]. MANUFACTURING TECHNOLOGY & MACHINE TOOL ,2007(12):31 一 33 [4] ZhangJinHuan . Structure of embedded digital control system and research on optimization of PID parameters of its servo. WuHan :School of Information Engineering, Wuhan University of Technology,2006 [5] Gloria AlessandroDe.MieroProeessor design for embedded system[J]. Journal of Systems Arehiteetufe , 1999.45:1139-1149 [6] Jean.J.Labrosse. Embedded Real-Time Operating System uc/os -Ⅱ [M]. ShaoBeibei. BeiJing :Beijing University of Aeronautics and Astronautics Press.2003:283-316. [7] LiFang , LiuKai , Wang TongTong.Implementation of Chinese Characters Display Module in Embedded CNC System Based on ARM[J].MANUFACTURING INFORMATION ENGINEERING OF CHINA , 2008(9):53-55 [8] Liao Xiao Guo.Zhu Qi Shu.Computer numerical control.WuHan : Huazhong University of Science.1999:78-95. [9] Liu BaoYan, ChengShuKang .Stepper motor and its drive control system.Harbin: Harbin Institute of Technology Press.1997:202-216. [10] Stylo , AW/Diana , GA low cost , high performance PC based integrated Real-time motion control development system.IEEE International Symposium on Industrial Eleetronies.Proeeedings.ISIE , 98.1998.Vol.1.PP127-130. 266
ISBN 978-952-5726-09-1 (Print) Proceedings of the Second International Symposium on Networking and Network Security (ISNNS ’10) Jinggangshan, P. R. China, 2-4, April. 2010, pp. 267-270 Parabola Interpolation With Adaptive Error Compensation Guangming Yang 1 , and Fengqi Yu 2 1,2 Department of Integrated Electronics,Shenzhen Institute of Advanced Technology, CAS Shenzhen, China, 518067 1 Email: mark111yang@hotmail.com 2 Email: fq.yu@siat.ac.cn Abstract—This paper proposes a novel scheme to interpolate images based on Lagrange Interpolation Theory. Parabola polynomial with an adaptive Lagrange error compensation is adopted to determine 1-D pixels. In order to predict 2-D pixels more accurately, the direction perpendicular to gradient vector is determined. To simplify the interpolation process, we give a range of the direction. Simulation results show that the proposed method can get clearer and sharper image than traditional methods. From objective point of view, average gradient and mean structural similarity (MSSIM) are calculated to demonstrate its superior to other methods. Index Terms -parabola interpolation, Lagrange interpolation error, Sobel operator, gradient direction , MSSIM. I. INTRODUCTION Image interpolation is a method to improve resolution of an image. It is widely applied in outer space image, medical image, and images in consumer electronics, etc. There are many image interpolation techniques, e.g. bilinear, cubic convolution [1], and bicubic B-spline interpolators. However, These techniques suffer from artifacts such as zigzag, ringing and blurriness. Especially the blurriness artifact blurs image detail so badly that we can’t do any further image analysis. Efforts have been made by many people to improve the image quality, Lei Zhang [6] proposed an interpolation algorithm based on directional filtering and data fusion, which can preserve the edge information to a certain extent. Schultz proposed MAP (maximum a posteriori) algorithm to expand image [4], which places the interpolation problem into a statistical framework. For the purpose of reducing the interpolation error, EASE method was proposed by Cha [2]. In his scheme, based on bilinear method, Lagrange interpolation error theory is used to compensate the pixel error in 1-D signal, which makes the pixel values more accurate. However, Zhang’s algorithm and MAP require more computations. Although EASE applies error compensation to interpolation successfully, the quality of the interpolated image cannot meet some requirements because it is based on biline method in 1-D. To further improve image resolution, we propose a parabola interpolation method which interpolates the 1-D direction pixels with a parabola interpolation polynomial, where an error compensation technique is considered. Then based on bilinear method, 2-D pixels along the direction perpendicular to gradient direction are interpolated. The gradient direction is calculated by vertical and horizontal Sobel operators. This paper is organized as follows: Section Ⅱ briefly describes the parabola interpolation and the error estimation theory. Section Ⅲ presents the proposed algorithm of 1-D and 2-D interpolation. Experiment results and performance analysis are presented in section Ⅳ , where average gradient and MSSIM quality assessment methods are adopted from objective point of view. A brief conclusion is presented in Section Ⅴ. II. REVIEW OF PARABOLA INTERPOLATION AND ERROR ESTIMATION As a special part of Lagrange interpolation, parabola interpolation polynomial L 2 (x) can be formulated as [5]: ( x−xk)( x−xk+ 1) ( x−xk− 1)( x−xk+ 1) L2() x = yk− 1 + yk ( xk− 1−xk)( xk− 1−xk+ 1) ( xk−xk− 1)( xk−xk+ 1) ( x−xk− 1)( x−xk) + yk + 1 ( xk+ 1−xk− 1)( xk+ 1−xk) (1) where each variable is interpreted in figure 1. x k −2 x k −1 f ( x) x x k x k + 1 x k + 2 Figure 1. Interpolation sketch map The value of x is estimated by the surrounding elements with corresponding weights. The interpolation error is discussed in ref. [5]. Assume f (n) (x) is continuous in the range x∈ [x 0 , x 1 ] , and f (n+1) (x) exists when x∈ (a, b), L n (x)is the interpolation polynomial. The interpolation error is: © 2010 ACADEMY PUBLISHER AP-PROC-CS-10CN006 267
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Proceedings The Second Internationa
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Table of Contents Message from the
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Zuming Xiao, Zhan Guo, Bin Tan, and
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Message from the Symposium Chairs T
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Second International Symposium on N
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model that can deal with time serie
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training for the Wushu competition
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information, called weak uncertain
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Student side Student side Student s
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for Imaging Two and Three Phase Flo
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A. Profiling&following control algo
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Research and Realization about Conv
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Ⅲ. AN IMPROVED DNA ALGORITHM FOR
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Ⅴ.CONCLUSION REMARKS DNA computer
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II. RELATED WORK A. Mobile Service
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special services. SOAP is used to b
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detection methods of DDoS attacks m
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Figure 1. An analysis of the partit
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distance of view point. Given that
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Ⅳ. EVALUATION OF BLENDED LEARNING
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symmetric with respect to the origi
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each sample belongs to each categor
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A. Data Preparing To generate our t
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Strong earthquake 0.1< M L
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indirect causes, and the logical re
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egression. Granger causality test i
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B. Evaluation We have evaluated thi
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TABLE I. DESCRIPTION OF PROPOSITION
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Figure 9. (a)the original image.(b)
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that studying being going to be to
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module, communication module, apper
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III. AUTONOMIC RESOURCE ALLOCATION
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Keyboard event Application User mod
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some drilling fluid produces hydrog
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esults of the spatial transform par
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B. Research on protocol actions Com
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ACKNOWLEDGMENT This work is funded
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[4] Huang, Hung, and J. Y. jen Hsu.
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ontology, and the domain dictionary
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