Pelco LPR-VS-VPS-PT-01 License Plate Recognition Software Toolkit
The Pelco LPR-VS-VPS-PT-01 is a software-based automatic license plate recognition (ALPR) system that integrates optical character recognition (OCR) engines to detect, capture, and catalog vehicle license plates in real time. Built for parking enforcement, traffic management, and vehicle access monitoring, this toolkit detects plates from moving vehicles up to 250 kph (150 mph) and reads rectangular, square, and multi-line plates (up to 3 lines) regardless of color scheme (dark-on-light, light-on-dark). The system compares captured plates against user-defined watchlists to identify VIP vehicles, suspects, and unauthorized access — then triggers operator alerts and maintains searchable plate logs.
Overview
VideoXpert Plates operates as either a standalone product via browser-based interface or as a plugin within the larger VideoXpert Video Management System ecosystem. The toolkit includes three core applications: VideoXpert Plates Manager (centralized plate image management, search, alerts, and metadata), VideoXpert Plates ALPR (real-time OCR engine), and VideoXpert Plates Plugin (integration into VideoXpert OpsCentral). Two deployment editions exist — Professional for parking and small-city applications, and Enterprise for larger municipal deployments with higher throughput demands.
Compatibility
The LPR-VS-VPS-PT-01 integrates with Pelco VideoXpert Video Management System environments via the included Plugin, or operates independently with IP cameras capable of streaming ONVIF-compliant video feeds (1280×720 minimum, 850nm IR Day/Night support). Supports simultaneous multi-country plate recognition — reads plates from the US, Canada, and international jurisdictions from a single camera feed. Capable of single- or dual-lane coverage from one camera, with directional filtering to capture traffic flowing in two directions simultaneously from one image stream. Can extract and read up to eight license plates on a single vehicle.
Installation Notes
Requires 8 GB RAM minimum with 1 GB per 16 GB additional RAM allocation. VideoXpert Plates Manager must be deployed on a Windows Server or compatible Windows machine with network access to the VideoXpert ecosystem. Configure network connectivity to IP cameras and ensure ONVIF protocol support on all source cameras. Plate accuracy depends on camera placement: optimal angle and distance to target vehicle improves OCR confidence. The system uses machine learning-based fuzzy logic matching to reconstruct damaged or obscured plates, compensating for carrier obstruction. Deploy Manager in a zone with reliable power and network redundancy for 24/7 enforcement operations.
