Inter-point envelope based distance moments for offline signature verification

In this paper, inter-point envelope based distance moments are proposed for offline signature verification. Two types of features such as the DC-line and envelope-to-envelope features are investigated from various known reference points. The detailed and high dimensional inter-point distances are used to estimate centralized moments such as the variance, skewness, kurtosis along with mean. The generated moment features are subsequently applied for training the SVM classifier. A newly suggested approach to generate the moment features by separately analyzing the upper and lower envelopes has shown high verification accuracy of 92.73% on the noisy CEDAR signature database.