论文标题
使用计算机视觉技术对图像的几乎重复检测的审查
A Review on Near Duplicate Detection of Images using Computer Vision Techniques
论文作者
论文摘要
如今，数字内容是广泛的，可以合法或非法重新分布。例如，在互联网上发布图像后，其他Web用户可以修改它们，然后重新播放其版本，从而生成近乎删除的图像。近乎解其物的存在会对搜索引擎的性能产生严重影响。计算机视觉涉及自动提取，分析和理解数字图像中有用信息。计算机视觉的主要应用是图像理解。图像理解中有几个任务，例如特征提取，对象检测，对象识别，图像清洁，图像转换等。在与图像的近乎重复检测有关的文献中没有适当的调查。在本文中，我们回顾了最先进的基于计算机视觉的方法和用于检测几乎重复图像的特征提取方法。我们还讨论了该领域的主要挑战，以及其他研究人员如何应对这些挑战。这篇评论为有兴趣在该领域工作的研究人员提供了研究指示。
Nowadays, digital content is widespread and simply redistributable, either lawfully or unlawfully. For example, after images are posted on the internet, other web users can modify them and then repost their versions, thereby generating near-duplicate images. The presence of near-duplicates affects the performance of the search engines critically. Computer vision is concerned with the automatic extraction, analysis and understanding of useful information from digital images. The main application of computer vision is image understanding. There are several tasks in image understanding such as feature extraction, object detection, object recognition, image cleaning, image transformation, etc. There is no proper survey in literature related to near duplicate detection of images. In this paper, we review the state-of-the-art computer vision-based approaches and feature extraction methods for the detection of near duplicate images. We also discuss the main challenges in this field and how other researchers addressed those challenges. This review provides research directions to the fellow researchers who are interested to work in this field.
