图像分析在汽车保险分诊中的新应用

Ying Li, C. Dorai
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引用次数: 5

摘要

对于汽车保险索赔流程而言,改进首次损失通知以及快速调查和评估索赔可以通过减少损失调整费用来推动重大价值。本文提出了一种将图像分析和模式识别技术应用于汽车损伤自动识别和表征的新方法。这方面的成功将使一些案件在没有人工理算员的情况下进行,而另一些案件则可以更有效地进行,从而最终缩短第一次损失通知和最终赔付之间的时间。为了验证其可行性,我们建立了一个基于事故前后汽车图像对比的自动识别受损区域的原型系统。在合理控制的环境下,用40辆比例模型汽车的图像对原型系统的性能进行了评估,获得了令人鼓舞的结果。我们相信,随着图像分析和模式识别技术的进步,所提出的想法可以演变成一个非常有前途的应用领域,汽车保险行业可以显著受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying Image Analysis to Auto Insurance Triage: A Novel Application
For the auto insurance claims process, improvements in the First Notice of Loss and rapidity in the investigation and evaluation of claims could drive significant values by reducing loss adjustment expense. This paper proposes a novel application where advanced technologies in image analysis and pattern recognition are applied to automatically identify and characterize automobile damage. Success in this will allow some cases to proceed without human adjusters, while others to proceed more efficiently, thus ultimately shortening the time between the first Notice of Loss and the final payout. To investigate its feasibility, we built a prototype system which automatically identifies the damaged area(s) based on the comparison of before-and after-accident automobile images. Performance of the prototype system has been evaluated on images taken from forty scaled model cars under reasonably controlled environments, and encouraging results were obtained. It is our belief that, with the advancement of image analysis and pattern recognition technologies, the proposed idea could evolve into a very promising application area where the auto insurance industry could significantly benefit.
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