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Computer Vision and Deep Learning technology are playing a key role in the development of Automatic Number Plate Recognition (ANPR) to achieve the goal of an Intelligent Transportation System (ITS). ANPR systems and pipelines presented in the literature often work on a specific layout of the number plate as every region has a unique plate configuration, font style, size, and layout formation. In this paper, we have developed a smart vehicle access control system considering a wide variety of plate formations and styles for different Asian and European countries and presented novel deep learning based ANPR pipeline that can be used for heterogeneous number plates. The presented improved ANPR pipeline detects vehicle front/rear view and subsequently localizes the number plate area using the YOLOv4 (You Only Look Once) object detection models. Further, an algorithm identifies the unique plate layout …