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Face Registration with Vigorous Improved M-Estimator

Tarun Motwani, Jamvant S. Kumare

Abstract


Vigorous face registration method based on Ali’s based M-Estimator (MCCA) is well-defined in this paper. A proficient valued mask function used in correlation is calculated by Ali, based vigorous statistics and used as a similarity measure to register images. The mask function is used to quashing the occlusion and as well as distant outliers, which are not controlled by the Huber based M-estimator usually. The supremacy of this algorithm is presented by this experimentation analysis and its correct result presentation in the dissimilar real situation images.

 

Cite this Article
Tarun Motwani, Kumare Jamvant S. Face Registration with Vigorous Improved M-Estimator. Journal of Image Processing & Pattern Recognition Progress. 2015; 2(3): 1–11p.


Keywords


Distant-outliers, cross correlation, Asad Ali based m-estimator, face registration

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References


Ghaffary BK, Sawechuk AA. A Survey of New Techniques for Image Registration and Mapping. Proceedings SPIE: Applications of Digital Image Processing. 1983; 432: 222–239p.

Brown LG. A Survey of Image Registration Techniques. ACM Comput Surv. 1992; 24: 326–376p.

Zitova B, Flusser J. Image Registration Methods: A Survey. Image Vision Comput. 2003; 21: 977–1000p.

Dai X, Khorram S. A Feature-Based Image Registration Algorithm using Improved Chain-Code Representation Combined with Invariant Moments. IEEE Trans Geosci Remote Sensing. 1999; 37: 2351–2362p.

Stockman G, Kopstein F, Benett S. Matching Image to Models for Registration and Object Detection via Clustering. IEEE Trans Pattern Anal Machine Intell. 1982; 4: 229–241p.

Goshtasby A, Stockman GC, Page CV. A Region Based Approach to Digital Image Registration with Sub Pixel Accuracy. IEEE Trans Geosci Remote Sensing. 1986; 24: 390–399p.

Sester M, Hild H, Fritsch D. Definition of Ground Control Feature for Image Registration using GIS Data Proceedings. ISPRS Commission III Symposium on Object Recognition and Scene Classification from Multispectral and Multisensor Pixels, OH. 1998; 537–543p.

Goshtasby A. Registration of Images with Geometric Distortions. IEEE Trans Geosci Remote Sensing. 1988; 26: 60–64p.

Flusser J, Suk T. A Moment Based Approach to Registration of Images with Affine Geometric Distortion. IEEE Trans Geosci Remote Sensing. 1994; 32: 382–387p.

Shekhar C, Govindu V, Chellapa R. Multisensor Image Registration by Feature Consensus. Pattern Recogn. 1999; 32: 39–52p.

Zhu M. Volume Image Registration by Cross-Entropy Optimization. IEEE Trans Med Imag. 2002; 21: 174–180p.

Pluim JPW, Maintz JBA, Viergever MA. Image Registration by Maximization of Combined Mutual Information and Gradient Information. IEEE Trans Med Imag. 2000; 19: 809–814p.

Roche A, Malandain G, Ayache N. Unified Maximum Likelihood Approaches in Medical Image Registration. Int J Imag Syst Tech. 2000; 11: 71–80p.

Viola P, Wells WM. Alignment by Maximization of Mutual Information. International Journal Computing. 1997; 24: 137–154p.

Wells W, Viola P, Atsumi H, et al. Multimodal Volume Registration by Maximization of Mutual Information. Med Image Anal. 1996; 1: 35–51p.

Maes F, Collignon A, Vanderneulen D, et al. Multimodality Image Registration by Maximization of Mutual Information. Proceedings Workshop on Mathematical Methods in Biomedical Image Analysis. IEEE Computer Society Press; 1996: 14–22p.

Barnea D, Silverman H. A Class of Algorithms of Fast Digital Image Registration. IEEE Trans Comput. 1972; 21: 179–186p.

Aggarwal JK, Davis LS, Martin WN. Correspondence Processes in Dynamic Scene Analysis. In Proceedings of the IEEE. 1981; 69: 562–571p.

Kaneko S, Murase I, Igarashi S. Robust Image Registration by Increment Sign Correlation. Pattern Recogn. 2002; 35: 2223–2234p.

Kaneko S, Satoh Y, Igarashi S. Using Selective Correlation Coefficient for Robust Image Registration. Pattern Recogn. 2003; 36: 1165–1173p.

Arya KV, Gupta P, Kalra PK, et al. Image Registration Using Robust M-Estimators. Pattern Recogn Lett. 2007; 28: 1957–1968p.

Huber PJ. Robust Statistics. NY: John Wiley & Sons; 1981.

Tukey JW. Exploratory Data Analysis. Cy: Addison-Wesley Publishers; 1977.

Rey WJJ. Introduction to Robust and Quasi-robust Statistical Methods. Berlin Heidelberg: Springer-Verlag; 1983.

Hampel FR, Ronchetti EM, Rousseeuw PJ, et al. Robust Statistics: The Approached Based on Influence Function. NY: John Wiley & Sons; 1986.

Black M, Rangarajan A. On the Unification of Line Processes, Outlier Rejection, and Robust Statistics with Applications in Early Vision. International Journal Computing. 1996; 19: 57–91p.

Andrews DF. A Robust Method for Multiple Linear Regression. Techni-metrics. 1974; 16: 523–531p.

Qadir MF. Robust Method for Detection of Single and Multiple Outliers. Scientific Khyber. 1996; 9: 135–144p.

Ali A, Qadir MF. A Modified M-estimator for the Detection of Outliers. PJSOR. 2005; 1: 49–64p.


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