Car Plate Recognition Tests
This research is dedicated to emerging area of human and machine quality optimization in video monitoring systems. Quality of Experience term in monitoring systems defines an ability to recognize some specific actions and detect some objects. New video quality recommendation will have to be developed in order to assure an acceptable level of recognition/detection accuracy. This involves video codec parameters adjustment and constant control with respect to the current video characteristics and intended recognition/detection actions.
The tests were performed using 30 source video sequences, each showing different car entering or leaving a parking lot. The cars used in the experiment are owned by INDECT and AGH employees. From all car owners a signed permission was received. The permission allows us to use the sequence for the research purpose and share it with the community. The example of the permission sheet (in Polish and English) is presented below:

The source sequences were 20 seconds long, GoP = 30, only I and P frames, 25 FPS, with average bitrate 10 Mbit/s. All video sequences were encoded using H.264/AVC video codec, x264 implementation. The following resolutions: 1280:720, 640:360, 704:576, 352:288 and the following quantization parameters QP were used: 33, 35, 37, 39, 41, 43, 45, 47, 49, 51. In the result of the above parameters selection each source sequence SRC 1-30 was encoded into 30 different versions HRC (Hypothetical Reference Circuit) 1- 30. The whole test set consist of 900 sequences.
The tests were performed using web-based interface. In the whole experiment complete answers from 30 tester were gather. Except the plate number, testers had also to specify car color and brand. It was possible to control a video sequences playback. Such actions as play, pause, stop, navigate, and enter full screen mode were allowed. Obtained results were store in a database for further processing purpose. The interface is presented on the picture below:

Obtained results require some processing including identification of reliable testers and results interpretation. The conclusions and results in a form of a guideline will be published soon on INDECT web portal.
Piotr Romaniak (AGH)
