Quality time-of-flight range imaging for feature-based registration using bacterial foraging

Image registration is a widely tackled research topic in the computer vision and the computer graphics fields. This problem aims to find an optimal transformation or correspondence between images acquired under different conditions. Recently, a new 3D image acquisition device based on the time-of-flight technology has appeared which obtains range images from real-time 3D video sequences. In this contribution, we aim to study the feasibility of using this new class of cameras to face the 3D model reconstruction procedure. Our proposal is two-fold. First, we introduce a novel image preprocessing pipeline in order to mage registration volutionary computation D modelling ime of flight acterial foraging improve the quality of time-of-flight range images and a subsequent feature extraction method considering both 2D and 3D images. As second major objective, we propose an adaptation of the evolutionary bacterial foraging optimization algorithm, which has recently emerged as a very powerful technique for real parameter optimization and gained a high interest for distributed optimization and control, to tackle the range image registration problem. Finally, we analyse the performance of our proposal against other state-of-the-art evolutionary image registration methods.