• M. L. Shahid Electronic Engineering Department, University of Engineering and Technology, Taxila, Chakwal Campus, Chakwal, Pakistan
  • G. Raja Electrical Engineering Department, University of Engineering and Technology, Taxila, Pakistan


Control Point Image Registration (CPIR) method is semi-automatic image registration technique in which control points are selected and matched manually. CPIR method is best suited for images that have distinct features; however, it needs highly skillful expert to select and match control points. This paper describes a modified CPIR method using fine tuning to register images which makes the control point selection and matching nearly independent of expert’s skills. Fine tuning is achieved by applying normalized cross correlation which selects an 11x11 window around the input image control point and a 21x21 template across the reference image control point. The results of modified CPIR method are analyzed and it is found that modified method is more suitable and has low spatial dispersion values as compared to CPIR method.


S. Damas, O. Cordón and J. Santamaría,

IEEE Computational Intelligence Magazine 6.

(2011) 26.

M.V. Wyawahare, P.M. Patil and H.K.

Abhyankar, International Journal of Signal

Processing, Image Processing and Pattern

Recognition 2 (2009) 11.

R.C. Gonzalez, R.E. Woods and S.L. Eddins,

Digital Image Processing Using MATLAB,

nd ed. (2010).

J.B.A. Maintz and M.A. Viergever, Medical

Image Analysis 2 (1998) 1.

M.J. Sullivan, A MATLAB-Based Image

Registration Graphical User Interface System

for P NMR and H MR Images of the Lower

Leg, Proc. of the 2010 IEEE 36th Annual

Bioengineering Conference, Northeast

(2010) 1-2.

MATLAB Documentation Web site. [Online].

tering-an-image.html (2012).

J.M. Fitzpatrick, D.L.G. Hill and C.R. Maurer,

Handbook of Medical Imaging – Medical

Image Processing and Analysis, SPIE Press,

(2009) 449.

B. Zitova´ and J. Flusser, Image and Vision

Computing 21 (2003) 977.

Y. Matsushita, K. Nishino, K. Ikeuchi and M.

Sakauchi, IEEE Transactions on Pattern

Analysis and Machine Intelligence 26 (2004)

L.A. Teverovskiy and O.T. Carmichael,

Feature-Based vs. Intensity-Based Brain

Image Registration: Voxel Level and

Structure Level Performance Evaluation,

Carnegie Mellon University (2006)




How to Cite

M. L. Shahid and G. Raja, “IMPLEMENTATION OF MODIFIED CONTROL POINT IMAGE REGISTRATION METHOD”, The Nucleus, vol. 50, no. 1, pp. 53–60, Mar. 2013.