Optimum Template Selection for Image Registration Using ICMM

1998 ◽  
Author(s):  
A. A. Y. Mustafa
Keyword(s):  
Image Registration ◽  
Template Selection ◽  
Selection For

scholarly journals Optimized Periocular Template Selection for Human Recognition

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Sambit Bakshi ◽  
Pankaj K. Sa ◽  
Banshidhar Majhi
Keyword(s):  
Feature Extraction ◽  
Biometric System ◽  
Human Recognition ◽  
Novel Approach ◽  
Database Size ◽  
Periocular Region ◽  
Template Selection ◽  
Selection For ◽  
Computationally Intensive

A novel approach for selecting a rectangular template around periocular region optimally potential for human recognition is proposed. A comparatively larger template of periocular image than the optimal one can be slightly more potent for recognition, but the larger template heavily slows down the biometric system by making feature extraction computationally intensive and increasing the database size. A smaller template, on the contrary, cannot yield desirable recognition though the smaller template performs faster due to low computation for feature extraction. These two contradictory objectives (namely, (a) to minimize the size of periocular template and (b) to maximize the recognition through the template) are aimed to be optimized through the proposed research. This paper proposes four different approaches for dynamic optimal template selection from periocular region. The proposed methods are tested on publicly available unconstrained UBIRISv2 and FERET databases and satisfactory results have been achieved. Thus obtained template can be used for recognition of individuals in an organization and can be generalized to recognize every citizen of a nation.

Research of Image Registration Based on Maximum Entropy Template Selection Algorithm

2011 ◽  
Vol 268-270 ◽  
pp. 1138-1143
Author(s):  
Hong Ying Qin
Keyword(s):  
Genetic Algorithm ◽  
Image Registration ◽  
Maximum Entropy ◽  
Evolutionary Process ◽  
Adaptive Genetic Algorithm ◽  
Image Stitching ◽  
Local Optimum ◽  
Selection Algorithm ◽  
Template Selection ◽  
Crossover And Mutation

This paper concerns an improved adaptive genetic algorithm, and the method is applied to the Maximum Entropy Template Selection Algorithm image registration. This method includes adjusting the probability of crossover and mutation in the evolutionary process. The method can overcome the disadvantage of traditional genetic algorithm that is easy to get into a local optimum answer. Results show our method is insensitive to the ordering, rotation and scale of the input images so it can be used in image stitching and retrieval of images & videos.

Automatic Parameter Selection for Multimodal Image Registration

2010 ◽  
Vol 29 (5) ◽  
pp. 1140-1155 ◽  
Author(s):  
Dieter A Hahn ◽  
Volker Daum ◽  
Joachim Hornegger
Keyword(s):  
Image Registration ◽  
Parameter Selection ◽  
Multimodal Image Registration ◽  
Selection For

Dynamic algorithm selection for multi-sensor image registration

2009 ◽  
Author(s):  
Stephen DelMarco ◽  
Victor Tom ◽  
Helen Webb ◽  
David Lefebvre
Keyword(s):  
Image Registration ◽  
Algorithm Selection ◽  
Dynamic Algorithm ◽  
Selection For
Sign in / Sign up

Export Citation Format

Share Document