License plate recognition system with improved recognition rate using inductive learning (IL) classification compared with support vector machine (SVM) based classification

To improve the license plate recognition accuracy rate using Inductive Learning (IL) classification using machine learning in comparison with Support Vector Machine (SVM) classifiers. Materials and Methods: The sample size of license plate recognition system with improved recognition rate was sample...

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Bibliographic Details
Main Authors: Kumar, Pavan, Thangaraj, S. John Justin
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Classification
Classifiers
License plates
Licenses
Machine learning
Recognition
Sensitivity analysis
Support vector machines
Online Access:Get full text
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Summary:To improve the license plate recognition accuracy rate using Inductive Learning (IL) classification using machine learning in comparison with Support Vector Machine (SVM) classifiers. Materials and Methods: The sample size of license plate recognition system with improved recognition rate was sample 2000 (Group 1 = 1500 and Group 2 = 1500). Comparative analysis of license plate recognition systems with improved recognition rate is performed by Support Vector Machine (SVM) whereas number of samples (N = 30) and Inductive Learning (IL) Classifier where number of samples (N = 30) techniques. Results: The accuracy rate of Support Vector Machine (SVM) is 96.34% whereas results of Inductive Learning (IL) accuracy rate are 91.87%. The Specificity rate is 96.43% for Support Vector Machine (SVM) whereas the results of Inductive Learning (IL) Specificity rate are 92.23%. The Sensitivity rate is 96.45% for Support Vector Machine (SVM) whereas results of Inductive Learning (IL) Sensitivity is 93.12%. There is a significant difference in accuracy rate with p value 0.0 in 2 tailed test (p
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0197424