scholarly journals HEURISTIC TECHNIQUES FOR HANDWRITTEN SIGNATURE CLASSIFICATION

2014 ◽  
pp. 87-92
Author(s):  
Marcin Adamski ◽  
Khalid Saeed
Keyword(s):  
Dynamic Time Warping ◽  
Experimental Techniques ◽  
Polar Coordinates ◽  
Time Warping ◽  
Boundary Tracing ◽  
Characteristic Features ◽  
Dynamic Time ◽  
Handwritten Signature ◽  
Slope Constraints

New theoretical and experimental techniques for offline classification of handwritten signatures are introduced in this paper. The proposed algorithms are mainly based on boundary tracing technique for extracting characteristic features. Outer and inner boundaries of the signature image are treated separately. The upper and lower parts of the boundaries are extracted to form two sequences of points. Three algorithms for calculating feature vectors are applied based on y coordinate, distances between consecutive points and from polar coordinates system. Experiments on classification of the resulted vectors were carried out by means of Dynamic Time Warping algorithm using window and slope constraints. A brief comparison between the authors' work and other known signature techniques is also discussed in the paper.

Continuous Motion Classification and Segmentation Based on Improved Dynamic Time Warping Algorithm

2017 ◽  
Vol 32 (02) ◽  
pp. 1850002 ◽  
Author(s):  
Mingqin Liu ◽  
Xiaoguang Zhang ◽  
Guiyun Xu
Keyword(s):  
Action Recognition ◽  
Dynamic Time Warping ◽  
The Other ◽  
Continuous Image ◽  
Single Image ◽  
Time Warping ◽  
Continuous Action ◽  
Template Sequence ◽  
Dynamic Time

The continuous image sequence recognition is more difficult than the single image recognition because the classification of continuous image sequences and the image edge recognition must be very accurate. Hence, a method based on sequence alignment for action segmentation and classification is proposed to reconstruct a template sequence by estimating the mean action of a class category, which calculates the distance between a single image and a template sequence by sparse coding in Dynamic Time Warping. The proposed method, the methods of Kulkarni et al. [Continuous action recognition based on sequence alignment, Int. J. Comput. Vis. pp. 1–26.] and Hoai et al. [Joint segmentation and classification of human actions in video, IEEE Conf. Computer Vision and Pattern Recognition, 2008, pp. 108–119.] are compared on the recognition accuracy of the continuous recognition and isolated recognition, which clearly shows that the proposed method outperforms the other methods. When applied to continuous gesture classification, it not only can recognize the gesture categories more quickly and accurately, but is more realistic in solving continuous action recognition problems in a video than the other existing methods.

Based on EADTW On-Line Handwriting Signature Handwriting Signature Verification System Design and Implementation

2014 ◽  
Vol 556-562 ◽  
pp. 5902-5905 ◽  
Author(s):  
Lei Ding ◽  
Yong Jun Luo ◽  
Yang Yang Wang ◽  
Zheng Li ◽  
Bing Yin Yao
Keyword(s):  
System Design ◽  
Dynamic Time Warping ◽  
Test Sample ◽  
Signature Verification ◽  
Time Warping ◽  
Design And Implementation ◽  
On Line ◽  
Dynamic Time ◽  
Handwritten Signature ◽  
New System

In view of poor accuracy and slow calculation of the traditional on-line handwriting signature verification, an on-line handwriting signature verification based on Early Abandon Dynamic Time Warping (EADTW) was designed and implemented after numerous researched. The training template followed the mechanism of benchmark signature, while the certification part adopted EADTW algorithm. The experimental results showed that compared with on-line handwritten signature system based on DTW (dynamic time warping), this new system not only greatly reduced cumbersome and repeated calculation, but also obviously improved the accuracy, The bigger the test sample is, the more obvious the advantage is.

Dynamic time warping based connectivity classification of event-related potentials

2019 ◽  
Author(s):  
Kadhum Kareem Al-rubaye ◽  
Oğuz Bayat ◽  
Osman Nuri Ucan ◽  
Dilek Göksel Duru ◽  
Adil Deniz Duru
Keyword(s):  
Dynamic Time Warping ◽  
Event Related Potentials ◽  
Time Warping ◽  
Related Potentials ◽  
Dynamic Time

scholarly journals Classification of genomic signals using dynamic time warping

2013 ◽  
Vol 14 (Suppl 10) ◽  
pp. S1 ◽  
Author(s):  
Helena Skutkova ◽  
Martin Vitek ◽  
Petr Babula ◽  
Rene Kizek ◽  
Ivo Provaznik
Keyword(s):  
Dynamic Time Warping ◽  
Time Warping ◽  
Dynamic Time ◽  
Genomic Signals
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