Motion Estimation in Medical Video Sequences Using Gabor Filter

Motion estimation is the process which determine motion vectors that describe the transformation from one 2D image to another from adjacent frames in a video sequence. It is the motion is in three dimensions but the images are a projection of the 3D scene onto a 2D plane. By motion estimation, we mean the estimation of the displacement or velocity of image structures from one frame to another in a time sequence of 2-D images. This projected motion is referred to as "apparent motion", "2-Dimage motion", or "optical flow”. Optical flow estimation, motion estimation, 2-D motion estimation, or apparent motion estimation have same meanings. The motion vectors may relate to the whole image (global motion estimation) or specific parts, such as rectangular blocks, arbitrary shaped patches or even per pixel. The motion vectors may be described by a translational model or many other models that can approximate the motion of a real video camera, such as rotation and translation in all three dimensions and zoom. Here we are going to present a noble technique by means of what we can predict motion in medical video sequences using Gabor filter. Gabor filters are band pass filters which are used in image processing for feature extraction, texture analysis, and stereo disparity estimation.