Object Detection and Optical Character Recognition for Automated Malaysia Driving License and Road Tax Document Details Retrieval

In the realm of automated document information extraction, Object Detection and Optical Character Recognition (OCR) approaches signify a pivotal leap forward. These advancements use machine learning and computer vision to quickly and precisely extract important data from a variety of document formats, including road tax and Malaysian driving license. Object Detection algorithms, with the help of platforms like Roboflow, can identify and localize key elements within documents, simplifying the dataset creation process for further analysis. Meanwhile, OCR technologies, such as Google Vision API, facilitate text and data extraction from images or scanned documents. This combination allows organizations to streamline document handling, eliminate manual processes, and reduce human errors associated with traditional data input methods. Moreover, sophisticated image classification techniques enhance document processing capabilities by improving the accuracy and reliability of extracted information. This integrated approach not only optimizes document management workflows but also sets the stage for developing advanced autonomous and assisted document technologies. As automated driving systems evolve, the seamless integration of Object Detection and OCR has the potential to revolutionize document handling through automated workflows and precise data extraction.