Comparison of ML algorithms for identification of Automated Number Plate Recognition

Automated Number Plate Recognition (ANPR) has become essential part of traffic control system because of unconstrained increased of vehicles on roads which make it difficult to control. On or after analysis of diverse author´s exertion, ANPR has six imperative parts like Image Acquisition, Pre-processing, edge detection, segmentation, feature extraction and recognition. Characters recognition is turn out to be difficult everyday jobs due to variations of number plate. The intentioned system is mainly focus on classification and recognition of characters using Kstar Machine learning algorithm. The classification characters present better performance using Kstar. A comparative study is done between these classifiers based upon their considerations like average accuracy, precision, recall and F-measure. Performance is deliberated using precision, recall and F-measure. The results give you an idea about that K STAR algorithm completes better with Recognition Rate and it achieved an accuracy of 99%.