Instrument Digital Image Recognition And Application Research

Instrument is used in measure system widely in many industries, as for some instruments that have no interface to send data, in order to automation, image sampling technique, image processing technique, image recognition technique and communication are required. So instrument recognition is very valuable.This thesis analyzes the current condition and development trend of digit recognition firstly, introducing the platform of hardware and software, facilitate the application research of digit recognition system. Image getting uses USB camera directly, cut down the cost in some degree. Some measures are taken to preprocess thermometer image, such as image enhance, image denoising, image segmentation and so on. Image gradient and previous experience technology are taken to segment image, the method is very effective. Edge detection and seed filling algorithm are taken to binarize the image, introducing canny operator and seed filling. This binarization method is precise and flexible, not only to normal image, but also to brighter and darker image. BP neural network is used to recognize digit, this improves the recognition rate.The object of this thesis is the digital image of thermometer having no data output interface and used in intelligent toilet, processing flowchart and steps are given, accomplishing data automatic sampling, having very high application value. In the digital image sampling, segmentation and binarization there is own characteristic.In the end of this thesis, concluding the total contents, pointing out the current problems to be resolved.