Performance Comparison of License Plate Recognition System Using Multi-Features and Svm

Feature extractor is one major factor in many image processing applications precisely in character recognition. the objective of this paper is to propose and to choose the best feature extractor for malaysian licence plate recognition system. an enhanced geometrical feature topological analysis is proposed as a feature extractor and support vector machine is used as the classification technique. the proposed techniques and known feature extractors were used to justify its robustness for license plate recognition problem in precise. previous research in the same domain, has applied straight pixels as the features. however, this approach is significantly acquire more time to execute the final recognition output typically in license plate recognition applications. consequently, an alternative called the geometrical features with various combination techniques are proposed to enhance the overall performance in license plate recognition.