This paper deals with a new integrated measurement method for application to a curved metal surface cutting system based on fuzzy inference. This system can recognize a measuring point on the object. This measurement system has two LED displacement sensors and two CCD cameras. The LED displacement sensor's spotlight is used for the active stereo sensing method. In addition, the LED displacement sensor's outputs are used for calibrating camera parameters. Therefore, we can calibrate the camera parameters easily. Then, we use neural networks to compensate the output of image processing for some errors, such as camera parameter error and lens distortion. By utilizing the neural networks, we can use as precise an image processing measurement system as possible. We use a multi-sensor integration system based on the fuzzy set theory. Fuzzy inference's input consists of information on the change in sensor output and the position change of the sensor system, together with the environmental data of a sensor. For this integration system, we can use the sensory system precisely. The proposed system is shown to be effective through extensive experimentation.