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User Authentication Through Pen Tablet Data Using Imputation and Flatten Function | IEEE Conference Publication | IEEE Xplore

User Authentication Through Pen Tablet Data Using Imputation and Flatten Function


Abstract:

Identifying a user or a person through handwriting-data is a popular technique. Many researches have been done in this area most of which are image or pattern-based analy...Show More

Abstract:

Identifying a user or a person through handwriting-data is a popular technique. Many researches have been done in this area most of which are image or pattern-based analysis. The accuracy level depends on the quality of the image or pattern. In this paper, we proposed user authentication system using an individual's pen tablet handwriting data. The proposed system is concerned with the numerical value of a person handwriting data getting from the digital pen and tablet device. Hence, user authentication through pen tablet data ensures more accuracy by working with user's real time handwritten data. In the proposed system, 24 persons writing samples(1262 .csv files and 23 class)are used for extracting features to identify a user based on their handwriting attributes. Six completely separated features are extracted after data analysis and pre-processing. The extracted features are mainly concerned with the vital attributes of a user's handwriting. The extracted features are used for classification. With this concern, we utilized different classification algorithms such as Support Vector Machine (SVM), Logistic Regression (LR), Linear Discriminant Analysis (LDA) and Random Forest (RF) classifier. From the implementation, different algorithms show different accuracy level. The testing accuracy rate of SVM, LR, LDA and RF is 87%, 85%, 76% and 77% respectively. The experimental analysis shows that we got more robust and satisfactory results which ensure the practicality of our system.
Date of Conference: 21-23 August 2020
Date Added to IEEE Xplore: 18 January 2021
ISBN Information:
Conference Location: Kaohsiung, Taiwan

References

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