首页> 外文会议>International conference on image analysis and recognition >Sunshine Hours and Sunlight Direction Using Shadow Detection in a Video
【24h】

Sunshine Hours and Sunlight Direction Using Shadow Detection in a Video

机译:视频中使用阴影检测的日照时间和阳光方向

获取原文

摘要

Previous systems used location information like GPS and the Suns location to detect sun light. However how much sunshine an area gets depends on its surround environment too, for instance we seldom get sunshine under a big tree or near a big building. So, we propose estimating sunshine hour just with a video by using image processing. We also calculate sunlight moving direction. One day outdoor video such as backyard, park or forest is processed to measure sunshine hour for every pixel to determine location of sunniest area. Shadow detection based on an algorithm using LAB color space where a difference in the light channel L is compared to neighbours to determine shadow. We improved this common algorithm by using adaptive threshold based on histogram of each frame of the video to overcome difficulty in tree and leaves shadow detection during sunset scene. We have tested 8 videos and the shadow detection rate has been improved to 93.04 from 85.34 by previously published algorithm. Then we use resultant image showing amount of sunlight on each pixel to obtain the sunshine hours. In addition, we calculate a sun direction from these images by using tracking algorithm for shadow movement.
机译:以前的系统使用诸如GPS和太阳位置之类的位置信息来检测太阳光。但是,一个区域获得多少阳光也取决于其周围环境,例如,我们很少在一棵大树下或一栋大建筑物附近获得阳光。因此,我们建议仅通过视频使用图像处理来估计日照时间。我们还计算日光的移动方向。处理诸如后院,公园或森林之类的一天户外视频,以测量每个像素的日照时间,以确定最阳光区域的位置。基于使用LAB颜色空间的算法进行阴影检测,在该算法中,将光通道L中的差异与相邻像素进行比较以确定阴影。我们通过使用基于视频各帧直方图的自适应阈值来改进此通用算法,以克服日落场景中树木和树叶阴影检测的困难。我们已经测试了8个视频,并且通过以前发布的算法,阴影检测率已从85.34提高到93.04。然后,我们使用显示每个像素上的日照量的结果图像来获得日照时间。此外,我们使用阴影移动跟踪算法从这些图像计算出太阳方向。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号