Detection of OCR Misclassifications in ALPR via Rapid Prototyping

Abstract

This paper originates from the limitations of traditional Optical Character Recognition (OCR) systems, particularly in recognizing multilingual texts (English and Thai characters) within Automatic License Plate Recognition (ALPR). A common challenge in current OCR models is character confusion, such as misreading between “0” and “O”, and “8” and “B,” which can significantly impact character recognition accuracy. Since OCR performance directly affects the overall effectiveness of ALPR systems, such misclassifications lead to incorrect vehicle identification. Therefore, this paper introduces a rapid prototyping approach for ALPR, focusing on multilingual license plates, especially Thai license plates that include both Latin (English) and non-Latin (Thai) characters. It aims to emphasize the identification and analysis of OCR misclassifications in how characters are recognized by OCR.