2017 6th International Conference on Systems and Control (ICSC)

2 / 2017-01-14 19:18:30

Concatenated Local Binary Patterns Descriptors Based Image Mosaicing Algorithm for UAV Images

1438,Image mosaicing, Harris,,CLBPD

UAV images are widely used in many applications,however, there are some problems with these images, e.g. the Field Of View (FOV) of UAV images is smaller than those of traditional aerial images, and also; the resolution of UAV images is less than those of aerial ones. As a solution for these problems, these images with small views can be mosaiced together in order to increase the visual field and the image resolution. The most important part of image mosaicing algorithm is to find out correspondence points between the split images. Different approaches were proposed for features matching task, but most of them takes a long calculation time; and with increasing image size; this time will be increased. Since the Local Binary Patterns Descriptors (LBPDs) provide good and robust description for the detected key-points in two overlapped images, fast and good features matching can be obtained using the measured Hamming distance between two CLBPDs. In this paper, some related works concerning some image mosaicing algorithms will be discussed in the state of the art, then we will illustrate the LBP method, after that; we will state our proposed image mosaicing algorithm, finally; we will give some results.