The signature verification is broadly used for personal identification. The person is identified automatically using signature verification method to avoid forgery persons. The signature verification is classified into the static method and the dynamic method. The static verification method is based on stored images and the dynamic verification method is based on dynamic features of the signature. The integer wavelet transformation method is used to identify the breath and height ratio of the signature features. In addition to that spurious noise also removed before extracting the signature feature. And the signature is isolated from the background of the images. The extracted feature is analyzed using integer wavelet transformation and a neural network is selected to decide according to that original and forgery signature. As compared with the conventional system the proposed found to be about 20% error ratio. The database SVC2004 is selected to verify the signature.

签名验证广泛用于个人识别。使用签名验证方法自动识别人员，以避免伪造人员。签名验证分为静态方法和动态方法。静态验证方法基于存储的图像，动态验证方法基于签名的动态特征。整数小波变换方法用于识别特征特征的呼吸比和高度比。除此以外，在提取签名特征之前还消除了杂散噪声。并且签名与图像背景隔离。使用整数小波变换分析提取的特征，并选择神经网络根据原始特征和伪造特征进行决策。与常规系统相比，所提出的误差率约为20％。选择数据库SVC2004来验证签名。