scholarly journals A Comprehensive Survey on On-line Handwriting Recognition Technology and its Real Application to the Nepalese Natural Handwriting

1970 ◽  
Vol 5 (1) ◽  
pp. 31-55 ◽  
Author(s):  
Santosh KC ◽  
Cholwich Nattee
Keyword(s):  
Dynamic Time Warping ◽  
Feature Vector ◽  
Handwriting Recognition ◽  
Recognition System ◽  
Time Warping ◽  
Real Application ◽  
Non Linear ◽  
Comprehensive Survey ◽  
On Line ◽  
Dynamic Time

Handwriting Recognition Technology has been improving much under the purview of pattern recognition and image processing since a few decades. This paper focuses on the comprehensive survey on on-line handwriting recognition system along with the real application by taking Nepali natural handwriting (a real example of one of the cursive handwritings). The survey mainly includes pre-processing, feature vector and similarity measures in between the non-linear 2D sequences of coordinates, and their effective applications. A very highlighting topic "Dynamic Time Warping Algorithm'' (DTW) is introduced, which has been popular in determining the distance between two non-linear sequences ranging from handwriting to speech recognition. Besides these contemporary research issues/areas, stroke number and order free Nepalese natural handwritten recognition system is presented in the second step. Writing one's own style brings unevenness in writing units, which is the most difficult part to classify. Writing units reveal number, shape, size, order of stroke, and speed in writing. Variation in the number of strokes, their order, shapes and sizes, tilting angles and similarities among characters from one another are the important factors, which are to be considered in classification for Nepali. This paper utilizes structural properties of those alphanumeric characters, which have variable writing units. It uses a string of pen tip's positions and tangent angles of every consecutive point as a feature vector sequence of a stroke. We constructed a prototype recognizer that uses the DTW algorithm to align handwritten strokes with stored strokes' templates and determine their similarity. Separate system is trained for original and preprocessed writing samples and achieved recognition rates of 85.87% and 88.59% respectively. This introduces novel real time handwriting recognition on Nepalese alphanumeric characters, which are independent of number of strokes, as well as their order. Key Words: Handwriting Recognition System; Pre-processing; Feature Vector; Dynamic Time Warping; Agglomerating Hierarchical Clustering; Nepali. DOI: 10.3126/kuset.v5i1.2845 Kathmandu University Journal of Science, Engineering and Technology Vol.5, No.1, January 2009, pp 31-55

scholarly journals On-line Signature Verification Based on Modified Dynamic Time Warping and Wavelet Sub-band Coding

2010 ◽  
pp. 210-219 ◽  
Author(s):  
Juan Carlos Sánchez-Diaz ◽  
Juan Manuel Ramírez-Cortes ◽  
Rogerio Enriquez-Caldera ◽  
Pilar Gomez-Gil
Keyword(s):  
Dynamic Time Warping ◽  
Signature Verification ◽  
Time Warping ◽  
On Line ◽  
Dynamic Time

scholarly journals Analisis Speaker Recognition Menggunakan Metode Dynamic Time Warping (DTW) Berbasis Matlab

AVITEC ◽  
2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Noor Fita Indri Prayoga
Keyword(s):  
Feature Extraction ◽  
Speaker Recognition ◽  
Dynamic Time Warping ◽  
Recognition Accuracy ◽  
Recognition System ◽  
Extraction Process ◽  
Test Results ◽  
Time Warping ◽  
Dynamic Time ◽  
The Voice

Voice is one of  way to communicate and express yourself. Speaker recognition is a process carried out by a device to recognize the speaker through the voice. This study designed a speaker recognition system that was able to identify speakers based on what was said by using dynamic time warping (DTW) method based in matlab. To design a speaker recognition system begins with the process of reference data and test data. Both processes have the same process, which starts with sound recording, preprocessing, and feature extraction. In this system, the Fast Fourier Transform (FFT) method is used to extract the features. The results of the feature extraction process from the two data will be compared using the DTW method. Calculations using DTW that produce the smallest value will be determined as the output. The test results show that the system can identify the voice with the best level of recognition accuracy of 90%, and the average recognition accuracy of 80%. The results were obtained from 50 tests, carried out by 5 people consisting of 3 men and 2 women, each speaker said a predetermined word

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.

scholarly journals Modified Dynamic Time Warping Based on Direction Similarity for Fast Gesture Recognition

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Hyo-Rim Choi ◽  
TaeYong Kim
Keyword(s):  
Gesture Recognition ◽  
Dynamic Time Warping ◽  
Spline Interpolation ◽  
Recognition System ◽  
Movement Direction ◽  
Time Warping ◽  
Suggested Algorithm ◽  
The Difference ◽  
Improved Performance ◽  
Dynamic Time

We propose a modified dynamic time warping (DTW) algorithm that compares gesture-position sequences based on the direction of the gestural movement. Standard DTW does not specifically consider the two-dimensional characteristic of the user’s movement. Therefore, in gesture recognition, the sequence comparison by standard DTW needs to be improved. The proposed gesture-recognition system compares the sequences of the input gesture’s position with gesture positions saved in the database and selects the most similar gesture by filtering out unrelated gestures. The suggested algorithm uses the cosine similarity of the movement direction at each moment to calculate the difference and reflects the characteristics of the gesture movement by using the ratio of the Euclidean distance and the proportional distance to the calculated difference. Selective spline interpolation assists in solving the issue of recognition-decline at instances of gestures. Through experiments with public databases (MSRC-12 and G3D), the suggested algorithm revealed an improved performance on both databases compared to other methods.

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