Advanced Driver Assistance Systems (ADAS) is a growing technology in automotive industry, intended to provide safety and comfort to the passengers with the help of variety of sensors like radar, camera, Light Detection and Ranging (LIDAR) etc. The camera sensors in ADAS used extensively for the purpose of object detection and classification which are used in functions like Traffic sign recognitions, Lane detections, Object detections and many more. The development and testing of camera-based sensors involves the greater technologies in automotive industry, especially the validation of camera hardware and software. The testing can be done by various processes and methods like real environment test, model-based testing, Hardware, and Software in loop testing. A fully matured ADAS camera system in the market comes after passing all these verification processes, yet there are lot of new failures popping up in the field with this ADAS system. Since ADAS is an evolving technology, many new field issues keep coming due to huge diversity of features in the real-world infrastructure. So, to bring up a more reliable ADAS system, validating every newly reported issue and including the fix in the software is the only way to bring the safe and reliable system in the Automobiles. If there is any issue reported in certain places, the current practice is to reproduce the issue in the same place, analyzing the issue & finding the solution with fix in the software and finally validating that issue in the same location. This process of reproducing the issue & validating the fix in the same location can become more complex and expensive since that hotspot locations can be found anywhere in the world. This paper proposes a technique for the camera-based testing includes maps-based testing by using real maps scenarios played in front of the camera in controlled simulation environment and evaluate the results to confirm the software maturity. Real world scenarios can be created using open-source maps data and using it after fine tuning in the Hardware in Loop (HiL) system can reduce the complexity and cost of development & validation of ADAS camera Sensors.