Monitoring Delay Automated Test System Based On Image Processing

With the development of society people's safety needs, security companies who engaged in video surveillance get a good opportunity for development. Now the requirement of the main decoding algorithm to equipments is high. Once the codec equipment can't meet the requirements, video delay may happen. In some application who need to monitor the movement of objects or require high real-time demand, this delay is not acceptable. So monitor delay is an important constraining factor in the development of monitoring system. Now most companies are using manual methods to test the monitor delay. In this paper, the author solved the automation problem of delay testing with the image processing technology and automated testing technology.Monitor delay Automation test system that was studied in the paper is a test tool, and run on H3C automation test platform, it provide network monitoring system time delay automation test for the company. The system consists of system control, environment configuration and image acquisition, image processing, the results generated. The system utilize the advantages of Matlab in algorithm design and debugging, AutoHotKey in interface automation, Python in automated testing and VC/SWIG in the interface conversion, so as to greatly reduce the system development cycle and make it easier to maintain.In the paper, considering features of the pictures that was collected in specific environment, the author improved image processing algorithm.Recognition accuracy:It achieve fine positioning for the target areas using the method that combined Geometry texture feature and Color characteristics.It located the right and left border of the target areas by Vertical projection statistics, and located top and bottom of the target areas by Scanning jump to change method.It made the character segmentation have stronger anti-noise and interference resistance ability that improved the Vertical projection statistics.Running speed:It enhanced the speed of morphological operation through the decomposition of structural elementsIt improved the speed of image gradient detection by the method that combined morphological operations and Houf transform.