摘要翻译：
实现支票自动识别系统的第一步之一是手写区域的提取。我们在本文中提出了一种混合方法来提取这些区域。该方法基于傅立叶描述子的数字识别和彩色图像处理的不同步骤。它要求对位于支票标记带上的代码进行银行识别，并用直方图差分法对手写颜色进行识别。然后利用数学形态学工具进行区域提取。
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英文标题：
《Extraction of handwritten areas from colored image of bank checks by an
  hybrid method》
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作者：
Sofiene Haboubi and Samia Maddouri
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最新提交年份：
2011
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  One of the first step in the realization of an automatic system of check recognition is the extraction of the handwritten area. We propose in this paper an hybrid method to extract these areas. This method is based on digit recognition by Fourier descriptors and different steps of colored image processing . It requires the bank recognition of its code which is located in the check marking band as well as the handwritten color recognition by the method of difference of histograms. The areas extraction is then carried out by the use of some mathematical morphology tools.
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PDF链接：
https://arxiv.org/pdf/1103.3420