Document Logo Detection and Recognition Using Bayesian Model

Hongye Wang
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引用次数: 22

Abstract

This paper presents a simple, dynamic approach to logo detection and recognition in document images. Although there are literatures on both logo detection and logo recognition issues, Current methods lack the adaptability to variable real-world documents. In this paper we initially observe this deficiency from a different point of view and reveal its inherent causation. Then we reorganize the structure of the logo detection and recognition procedures and integrate them into a unified framework. By applying feedback and selecting proper features, we make our framework dynamic and interactive. Experiments show that the proposed method outperforms existing methods in document processing domain.
基于贝叶斯模型的文档标识检测与识别
本文提出了一种简单、动态的文档图像标识检测与识别方法。虽然在标识检测和标识识别方面都有相关的研究,但目前的方法缺乏对多变的现实世界文档的适应性。本文从不同的角度对这一缺陷进行了初步观察,并揭示了其内在原因。然后我们重新组织了标识检测和识别程序的结构,并将它们整合到一个统一的框架中。通过应用反馈和选择适当的特征,我们使我们的框架具有动态性和互动性。实验表明,该方法在文档处理领域的性能优于现有方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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