A Performance Evaluation of a Real-time Image Mosaicing with a Rapid Prototype Hardware

The Field-Of-View(FOV) of compact cameras are very less compared to the FOV of humans. A single shot of capturing compact camera sensor does not capture the scenes as the human's vision. Mosaicing is a procedure of uniting the partial parts of a scene to form a large image that represents the whole scene. The main aim of mosaicing is to increase the FOV and to trace the path of any moving objects. In this paper, a real-time mosaicing is implemented with the various algorithms and compared with the proposed algorithm. The proposed method is a combination of FAST detector and Steerable filters. All the algorithms are executed with the multiple rapid prototype hardware's and compared their performance in terms of many parameters like corner detection rate, image mosaicing time, video mosaicing execution time. Geekbench mark test of having various parameters is conducted on three hardware's. Experimental results proved that the intel compute stick and Lenovo Ideacentre 300 hardware have high mobility to capture the remote areas of a scene or low altitude images to construct the mosaic image.