Panoramic Image Generation Algorithm based on Hu’s Moment Invariants

Abstract

The construction of large, high-resolution image is an active area of research in the fields of computer vision, image processing, and computer graphics. A Panorama is the process of combining multiple images with overlapping fields of view to produce a panorama. It is possible to produce a complete view of an area or location that cannot fit in a single shot. In this paper a high performance method for generating panoramic image is introduced. The process to generate a panoramic view can be divided into three main components: image acquisition, image registration, and merging. Geometric moment invariant produces a set of feature vectors that are invariant under shifting, scaling and rotation. The technique is widely used to extract the global features for pattern recognition due to its discrimination power and robustness. In this paper, moment invariant is used to determine the locations of merging the images to produce the panorama. The final step is adjusting the colors of the merged images. The results of experiments conducted on images taken by camera and test images loaded from the internet. The results show that the proposed algorithm is fast and efficient.