Traditionally, whiteboards have been used to brainstorm, teach, and convey ideas with others. However distributing whiteboard content remotely can be challenging. To solve this problem, A multi-camera system was developed which can be scaled to broadcast an arbitrarily large writing surface while removing objects not related to the whiteboard content. Related research has been performed previously to combine multiple images together, identify and remove unrelated objects, also referred to as foreground, in a single image and correct for warping differences in camera frames. However, this is the first time anyone has attempted to solve this problem using a multi-camera system. The main components of this problem include stitching the input images together, identifying foreground material, and replacing the foreground information with the most recent background (desired) information. This problem can be subdivided into two main components: fusing multiple images into one cohesive frame, and detecting/removing foreground objects. for the first component, homographic transformations are used to create a mathematical mapping from the input image to the desired reference frame. Blending techniques are then applied to remove artifacts that remain after the perspective transform. For the second, statistical tests and modeling in conjunction with additional classification algorithms were used.