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    • 1. 发明授权
    • Handwriting recognition training and synthesis
    • 手写识别训练与综合
    • US07657094B2
    • 2010-02-02
    • US11321493
    • 2005-12-29
    • Zhouchen LinLiang WanChun-Hui HuJian Wang
    • Zhouchen LinLiang WanChun-Hui HuJian Wang
    • G06K9/00
    • G06K9/42G06K9/00416G06K2209/01
    • Methods and systems for converting text into natural personal handwriting are provided. One aspect relates to the training of a computer to recognize a user's handwriting style. In one embodiment, the computer receives handwriting samples of at least one character written by the user, such as the character being provided as the beginning, middle, or ending character among a plurality of other characters. Further embodiments allow for increased personalization of the handwriting. Another aspect relates to system and methods for displaying a representation of a computer user's handwriting. In one embodiment, the handwriting comprises variant shapes of letters, personalized connection style between letters, and connection parts that look pressure-sensitive. In another embodiment, characters are adjusted, such as cutting portions of the character to create a more realistic recreation and synthesis of the handwriting.
    • 提供了将文本转换为自然人手写的方法和系统。 一方面涉及计算机的训练以识别用户的手写风格。 在一个实施例中,计算机接收由用户写入的至少一个字符的笔迹样本,诸如被提供为多个其他字符中的开始,中间或结束字符的字符。 进一步的实施例允许增加笔迹的个性化。 另一方面涉及用于显示计算机用户手写表示的系统和方法。 在一个实施例中,笔迹包括字母的变形形状,字母之间的个性化连接样式以及看起来对压力敏感的连接部分。 在另一个实施例中,字符被调整,例如切割角色的部分以创建更实际的娱乐和手写的合成。
    • 2. 发明申请
    • Handwriting recognition training and synthesis
    • 手写识别训练与综合
    • US20070154094A1
    • 2007-07-05
    • US11321493
    • 2005-12-29
    • Zhouchen LinLiang WanChun-Hui HuJian Wang
    • Zhouchen LinLiang WanChun-Hui HuJian Wang
    • G06K9/00G06K9/18
    • G06K9/42G06K9/00416G06K2209/01
    • Methods and systems for converting text into natural personal handwriting are provided. One aspect relates to the training of a computer to recognize a user's handwriting style. In one embodiment, the computer receives handwriting samples of at least one character written by the user, such as the character being provided as the beginning, middle, or ending character among a plurality of other characters. Further embodiments allow for increased personalization of the handwriting. Another aspect relates to system and methods for displaying a representation of a computer user's handwriting. In one embodiment, the handwriting comprises variant shapes of letters, personalized connection style between letters, and connection parts that look pressure-sensitive. In another embodiment, characters are adjusted, such as cutting portions of the character to create a more realistic recreation and synthesis of the handwriting.
    • 提供了将文本转换为自然人手写的方法和系统。 一方面涉及计算机的训练以识别用户的手写风格。 在一个实施例中,计算机接收由用户写入的至少一个字符的笔迹样本,诸如被提供为多个其他字符中的开始,中间或结束字符的字符。 进一步的实施例允许增加笔迹的个性化。 另一方面涉及用于显示计算机用户手写表示的系统和方法。 在一个实施例中,笔迹包括字母的变形形状,字母之间的个性化连接样式以及看起来对压力敏感的连接部分。 在另一个实施例中,字符被调整,例如切割角色的部分以创建更实际的娱乐和手写的合成。
    • 8. 发明申请
    • Signature verification
    • 签名验证
    • US20070154071A1
    • 2007-07-05
    • US11321232
    • 2005-12-29
    • Zhouchen LinLiang WanBin Wan
    • Zhouchen LinLiang WanBin Wan
    • G06K9/00
    • G06K9/00181
    • Methods and systems for training a computer to recognize and verify an individual's signature are provided. One illustrative method extracts a plurality of both global and local features from a relatively small sample of handwriting samples. In one such embodiment, only 5 samples are needed from an individual without requiring forgeries. In yet another embodiment, only three global parameters are utilized, thus reducing the complexity, and processing power, of the system. Utilizing such few global parameters also facilitates fine tuning of the systems. Further aspects of the invention relate to a multi-stage statistical system for on-line signature verification. In one embodiment, the system may comprise a simplified GMM model built on global signature properties and a left-to-right HMM model based on segmental features. In one embodiment, specific strategies are utilized to create model simplification and initialization in contrast to general GMM and HMM models.
    • 提供了用于训练计算机以识别和验证个人签名的方法和系统。 一个说明性方法从相对较小的笔迹样本样本中提取多个全局和局部特征。 在一个这样的实施例中,仅需要5个样本,而不需要伪造。 在另一个实施例中,仅使用三个全局参数,从而降低系统的复杂性和处理能力。 利用这么少的全局参数也有助于系统的微调。 本发明的其它方面涉及用于在线签名验证的多阶段统计系统。 在一个实施例中,系统可以包括基于全局签名特性的简化GMM模型和基于段特征的从左到右HMM模型。 在一个实施例中,与通用GMM和HMM模型相反,具体策略被用于创建模型简化和初始化。
    • 10. 发明授权
    • Signature verification
    • 签名验证
    • US07529391B2
    • 2009-05-05
    • US11321232
    • 2005-12-29
    • Zhouchen LinLiang WanBin Wan
    • Zhouchen LinLiang WanBin Wan
    • G06K9/00G06K9/46
    • G06K9/00181
    • Methods and systems for training a computer to recognize and verify an individual's signature are provided. One illustrative method extracts a plurality of both global and local features from a relatively small sample of handwriting samples. In one such embodiment, only 5 samples are needed from an individual without requiring forgeries. In yet another embodiment, only three global parameters are utilized, thus reducing the complexity, and processing power, of the system. Utilizing such few global parameters also facilitates fine tuning of the systems. Further aspects of the invention relate to a multi-stage statistical system for on-line signature verification. In one embodiment, the system may comprise a simplified GMM model built on global signature properties and a left-to-right HMM model based on segmental features. In one embodiment, specific strategies are utilized to create model simplification and initialization in contrast to general GMM and HMM models.
    • 提供了用于训练计算机以识别和验证个人签名的方法和系统。 一个说明性方法从相对较小的笔迹样本样本中提取多个全局和局部特征。 在一个这样的实施例中,仅需要5个样本,而不需要伪造。 在另一个实施例中,仅使用三个全局参数,从而降低系统的复杂性和处理能力。 利用这么少的全局参数也有助于系统的微调。 本发明的其它方面涉及用于在线签名验证的多阶段统计系统。 在一个实施例中,系统可以包括基于全局签名特性的简化GMM模型和基于段特征的从左到右HMM模型。 在一个实施例中,与通用GMM和HMM模型相反,具体策略被用于创建模型简化和初始化。