Khan Mohammad A U, Niazi Muhammad Khalid Khan, Khan Muhammad Aurangzeb
Department of Computer Engineering, Kyung Hee University, Sochen-dong, 449-701 Suwon, Korea.
IEEE Trans Image Process. 2006 Nov;15(11):3540-9. doi: 10.1109/tip.2006.877517.
In general, online signature capturing devices provide outputs in the form of shape and velocity signals. In the past, strokes have been extracted while tracking velocity signal minimas. However, the resulting strokes are larger and complicated in shape and thus make the subsequent job of generating a discriminative template difficult. We propose a new stroke-based algorithm that splits velocity signal into various bands. Based on these bands, strokes are extracted which are smaller and more simpler in nature. Training of our proposed system revealed that low- and high-velocity bands of the signal are unstable, whereas the medium-velocity band can be used for discrimination purposes. Euclidean distances of strokes extracted on the basis of medium velocity band are used for verification purpose. The experiments conducted show improvement in discriminative capability of the proposed stroke-based system.
一般来说,在线签名捕捉设备以形状和速度信号的形式提供输出。过去,在跟踪速度信号最小值时提取笔画。然而,得到的笔画形状更大且复杂,因此使得生成判别模板的后续工作变得困难。我们提出了一种新的基于笔画的算法,该算法将速度信号分割成不同的频段。基于这些频段,提取出本质上更小且更简单的笔画。对我们提出的系统进行训练发现,信号的低速和高速频段不稳定,而中速频段可用于判别目的。基于中速频段提取的笔画的欧几里得距离用于验证目的。所进行的实验表明,所提出的基于笔画的系统的判别能力有所提高。