Improved Harris Corner Detector Algorithm for Image Co-Registration

Image registration is the process of removing the offset between two or more images of the same location from different angles. One of the two images is the master image and the other is the slave image. In this paper an effective algorithm is proposed to align the two images; this algorithm is based on combining both area-based methods and feature-based methods. Cross-correlation function is used to detect the coarse offset between the master image and the slave image, while the fine offset between the two images is detected by the Harris corner detector [1] and Scale-Invariant Feature Transform (SIFT) which is proposed by Lowe (1999). Random Sample Consensus (RANSAC) algorithm [2] is used to estimate the transformation model. The proposed algorithm is evaluated by using the coherence map. The results show that the proposed algorithm is more effective than using the automatic image registration methods alone [3].