System and information security is becoming increasingly important in the information society. Personal authentication is becoming necessary in more and more fields. The traditional personal authentication methods cannot keep up with the development of the society because of their inherent defects. Under such circumstance, biometrics emerged as the time requires.Biometrics are the technologies that analyze human characteristics for automated personal authentication. Many common biometric features, such as fingerprint, face, iris, palmprint, voice, signature etc., have the properties that they are possessed by everyone, are different with different person and keep stable in a long period. They cannot be stolen nor lost, fake and are difficult to be forged or imitated. Therefore, they are very suitable for the personal authentication.Online handwritten signature verification is an important branch of biometrics. Handwritten signature has its own virtues: handwritten signature has been a human behavior characteristic and been widely accepted and applied since ancient times; online signature capture devices are much cheaper than iris and palmprint devices; handwritten signature is more difficult imitated than other personal physical characteristics. Therefore, online handwritten signature verification is hotspot in the biometrics field.The main purpose of this dissertation is to research the technology of parameter-based online signature verification. The research includes following parts:1. Online signature verification based on improved dynamic time warping and the elastic matching of 1D curve segments. An online signature can be considered as a point sequence with a same interval, and can be described by several 1D curves after some simple transformations. The segmentation and feature description of a 1D curve is very simple. It is very easy to separate a signature into several curves with different stableness by this 1D description. In the verification, different curves are given different weights. Because a 1D segment contains not only the features of the endpoints but the inner feature of