2 / 2017-01-14 19:18:30
Concatenated Local Binary Patterns Descriptors Based Image Mosaicing Algorithm for UAV Images
1438,Image mosaicing, Harris,,CLBPD
摘要录用
Mahmoud Belhocine Belhocine / CDTA
Abdelhai Lati Lati / USTHB
Noura Achour Achour / USTHB
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.
重要日期
  • 会议日期

    05月07日

    2017

    05月09日

    2017

  • 02月15日 2016

    初稿录用通知日期

  • 03月05日 2016

    终稿截稿日期

  • 01月15日 2017

    初稿截稿日期

  • 05月09日 2017

    注册截止日期

主办单位
Society of Development of Science and Novel Technologies
历届会议
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