کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
534075 | 870216 | 2012 | 6 صفحه PDF | دانلود رایگان |
Image registration is present in many computer vision and computer graphics real-world applications. Specifically, it plays a crucial role within the 3D digital model acquisition pipeline, in which the iterative closest point (ICP) algorithm is considered the de facto standard for pair-wise alignment of range images. Nevertheless, the success of ICP depends on several assumptions. A new family of registration techniques have been recently proposed based on evolutionary computation paradigm to solve the common ICP problems.Unlike previous contributions, we propose a novel self-adaptive evolutionary image registration algorithm able to search for the values of both the control and the problem solving parameters to achieve accurate alignments, simultaneously. It combines two different population-based optimization approaches that are concerned with the proper optimization of the control parameters and the image alignments, respectively. The performance of our proposal is compared with several state-of-the-art image registration methods.
► IR aims to find a geometric transformation between two or more images.
► In the last decade, the application of evolutionary algorithms to IR has caused an outstanding interest.
► We propose a new self-adaptive evolutionary approach to tackle IR.
Journal: Pattern Recognition Letters - Volume 33, Issue 16, 1 December 2012, Pages 2065–2070