| Automobile cluster centralizes the clusters of cars. It seems like a window that displays the operation status of cars. Although every cluster has its own feature, there are speedometer, tachometer, temperature gauge, fuel pressure gauge and warning telltales in the cars. Before the clusters from the workshops fix into the vehicle, there must be some testing and checking, including FCT-Function Circuit Test, pointer calibration, configure clusters'memories, quality final examination which involve in the following items: (1) checking pointers in those gauge and detecting the position errors, and by the way of cluster communication making sure that this errors are in acceptable scope, then burning the values into clusters; (2) checking all the warning lights and background lights, making sure that none of them has been damaged or missed, and none of them has been replaced by different color, testing electrical current of telltales.Commonly, these tests are accomplished by workers who detect the position of pointer and chaplet. Then it is adjusted to wanted scale by manual. Workers judge the color and brightness of them, and find out other visible defect. In this way, the result will be infected by several subjective elements such as the difference of angle and distance when watching cluster, and the fatigue of operator. Instead of machine vision, this thesis can test clusters automatically by computer vision technology. This way, the errors made by operators will be avoided, and the efficiency and accuracy will be improved. Along with popularization and improvement of machine vision, the cost of automatic calibration will be dramatically dropped.In this thesis, computer vision technology is used to develop auto-testing system of Ford cluster based on LabVIEW software platform. At the beginning, the thesis introduces the developing history of clusters and machine vision, as well as indicates some basic frames and imagine. In chaplet 2 it builds the whole hardware platform of system, and describe vision system, clusters'position and clamping system, and platform for communication between clusters and computers one by one. Chaplet 3 is one of the central parts of the thesis. In this chaplet, it introduces two methods to dealing with vision analyses according to Ford cluster itself. The main research work of this chaplet is generalized as following:Two methods are used to separate background and pointer. Then by edge scanning it gets the edge pointes and of pointer and integrate the line as framework line of pointer.It takes use of two different threshold methods to binary pointer. After removing impurity and morphology analyses, the thesis handles geometry operation to get the line of cluster according to the vision information.The center of the gauge is confirmed by two different position of pointer.A new method is proposed to develop the software of auto-testing system of automobile cluster which take advantage of known knowledge which is contained in kind of cluster template. In this way the efficiency of testing is improved. And what's more it can make it easier and quicker to develop system for a different kind of cluster.Methods proposed in this thesis have been proved by practice and experiment. The way to develop the software by using cluster template can improve efficiency of software developing and cluster testing. At the end, the thesis introduces the developing tool and environment also the thinking in developing the system.
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