Sub-surface information during a laparoscopic surgery is captured with a near infrared imaging where the tissue is highlighted with the help of an indocyanine dye injected to the patient before the surgery. The surgeons can use such system during the surgery, however, they need to swap the light source between infra-red and the white light to complete the surgery. Swapping the light source causes inconvenience and increase in the time of the surgery. The current study aims to develop a method for superimposing and tracking the infrared imagery on the laparoscopic video acquired under white light. In this study, the infrared imagery was captured and registered to one of the white light imagery from the endoscope video using a 2D image registration technique. The registration technique was based on maximization of mutual information between two images. The edges on the registered infrared image was detected using canny edge detection algorithm. A homography matrix between consecutive video frames under white light was calculated after characteristic feature point detection and matching. The homography matrix was applied on the registered infrared image (only edge) and a new registered edge image was generated. The process continued for every new frame of the video under white light. The system was applied with a video acquisition rate of 20 frames per second. The system needs to be evaluated for its influence on the time of surgery.