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A Colour Code Algorithm For Signature Recognition

机译：用于签名识别的颜色代码算法

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The paper ";A Colour Code Algorithm for Signature Recognition"; accounts an image processing application where any user can verify signature instantly. The system deals with a Colour code algorithm, which is used to recognize the signature. The paper deals with the recognition of the signature, as human operator generally make the work of signature recognition. Hence the algorithm simulates human behavior, to achieve perfection and skill through AI. The logic that decides the extent of validity of the signature must implement Artificial Intelligence Pattern recognition is the science that concerns the description or classification of measurements, usually based on underlying model. The measurement or the properties used to classify the objects are called as 'features', and the types or categories into which they are classified are called as classes. Since most pattern recognition tasks are first done by humans and automated later, the most fruitful source of features has been to asked the people who classify the objects how they tell them a part. The two main approaches to pattern recognition are the statistical (decision theoretic) and the syntactic approaches. Signature recognition is the best example of this fact. The algorithm is tested on various operating systems & we find that it works very well & satisfactory. While implementing the recognition process, we have used quite simpler way. At this stage we are getting accuracy up to about 80% to 90%. These conclusions are made on the basis of testing of 300 person's database. keywords: Signature Recognition, Image Morphology, Syntactic Pattern Recognition
机译：论文“;用于签名识别的颜色代码算法”;帐户一个图像处理应用程序，任何用户都可以在其中立即验证签名。系统处理颜色代码算法，该算法用于识别签名。由于人类操作员通常会进行签名识别，因此本文主要讨论签名的识别。因此，该算法模拟了人类的行为，以通过AI实现完美和技能。决定签名有效性范围的逻辑必须实现人工智能模式识别，这是一门与测量描述或分类相关的科学，通常基于基础模型。用于对对象进行分类的度量或属性称为“功能”，将对其进行分类的类型或类别称为类。由于大多数模式识别任务首先是由人完成的，后来又自动化了，所以功能最丰富的资源就是询问对对象进行分类的人如何区分对象。模式识别的两种主要方法是统计方法（决策理论）和句法方法。签名识别是这一事实的最好例证。该算法已在各种操作系统上进行了测试，我们发现它运行良好且令人满意。在实施识别过程时，我们使用了相当简单的方法。在此阶段，我们的准确度可达80％到90％。这些结论是在对300人的数据库进行测试的基础上得出的。关键词：签名识别图像形态学句法模式识别

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