Content-free image orientation detection using Local Binary Pattern

Image orientation detection is a basic, but important subject in image processing. It is also a difficult task because of the uncertainty of the context information of the image and the illumination. In this paper, we present a theoretically and computationally simple yet efficient content-free image orientation detection approach. The proposed approach is based on Local Binary Patterns which is recognized as gray scale and rotation invariant. By using the binary mode and the histogram computed over the overlapping region of two images, the experiments show that it can get excellent results in both artificial and real images. Furthermore, the method can be used in different images with similar contents. Through optimization, the run time of the algorithm reduces by a large amount and makes it applicable in real applications.