一种基于纹理和加权速度的集装箱图像快速拼接方法

Quanling Meng, Mengqin Zhang, W. Zhang
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引用次数: 1

摘要

随着海洋经济的快速发展,大量的集装箱运输到世界各地。为了降低集装箱在运输过程中损坏的风险,现有的解决方案主要依靠人工在集装箱进入码头之前或之后观察集装箱的外观,这种方法既耗时又不准确。为了解决这一问题,开发一种基于计算机视觉技术的集装箱损伤自动检测框架是一种智能方法。但是如何获取集装箱损伤检测的全景图像是一个具有挑战性的问题。本文以集装箱监控视频为基础,利用纹理特征对集装箱图像进行拼接,开发了集装箱全景实时生成系统。当没有可靠的偏移时,采用加权速度进行拼接。实验结果表明,所开发的系统能够实时地取得满意的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fast stitching method for container images using texture and weighted speed
With the rapid development of oceans economy, a huge number of shipping containers are transported all around the world. To reduce the risk of container damages during the transportation, existing solution relies mainly on human beings to observe the container appearance before or after it enters a dock, which is time-consuming and inaccurate. To solve this problem, one intelligent approach is to develop an automatic container damage detection framework based on computer vision techniques. But how to obtain the panorama images for container damage detection is a challenging issue. In this paper, a real-time container panorama producing system is developed based on container surveillance videos, which is implemented by container image stitching with texture features. When there is no reliable offset, the weighted speed for splicing is used. Experimental results indicate that the developed system could achieve approving results in a real-time manner.
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