The recent decades have experienced rapid growth of cities, their populations and the number of vehicles, which however has caused an upsurge of parking space problems in cities and eventually led to traffic congestion and waste of limited resources of parking spaces. The present research offers a new vision in resolving this problem by combining computer vision and perspective transformation in real time for parking management. The system used side view cameras and geometric transformation in order to view parking spaces from the non-conventional camera angles and even the position of the parking space itself. One of the significant advances is the concept of a comprehensive system of management of dispersed private and public parking lots targeting fragmentation of parking infrastructure within urban centres. The solution applies imaging and diagnostic algorithms for vehicle detection and tracking in real time, where information was adapted to the input for each of the vehicle types including cars, motorcycles, and three wheeled vehicles. The system makes use of perspective transformation and dynamic allocation of spaces to map and manage parking spaces and provides live information about available spaces to end users. The results from the study revealed increased parking space utilisation levels and decreased parking space search times which, in turn reduced the congestion levels of traffic. The research addresses critical gaps in existing parking management systems, particularly in handling multiple vehicle types and integrating diverse parking spaces within the urban environment.