The Research On Container Automatic Equipment Identification System

Container Automatic Equipment Identification (AEI) system can be widely applied to material circulation monitoring system in customs, to container management system in harbor bureau, container depot, and transportation industry, and to monitoring and management system in machining center, etc. Container AEI system based on Optical Character Recognition (OCR) technology makes use of image processing technology to extract and recognize characters of container codes automatically. On account of the advantages that such system doesn't need to attach any other equipment on container when recognizing, and its performance can be improved by means of manual operation through the user interface of computer terminal, it is developed rapidly and attached great importance by people increasingly.In this thesis, the container AEI system based on OCR technology is investigated. First, the working principle of the system is introduced and the characteristics of container's original image is analyzed. Then the process procedures are discussed in detail, which include image preproccss, localization and threshold of container codes region, characters segmentation, recognition preproccss, feature extraction and recognition. In image preprocessing, image quality is improved by using mathematical morphology to remove background of the image, making gray-scale transformation to enhance contrast and smoothing processing to filter noise. After image preprocessed, its edge is detected, and some long lines in edge image are filtered, and then mathematical morphology is employed to remove edge noise. Considering the characteristic of characters arrayed concentrated, the method that how to make use of character edge and mathematical morphology to locate container codes is described. The gray image in characters area is converted to binary one by suitable threshold. The segmentation technology that combines the technologies of getting connected region and projecting can be used to segment characters. Finally, characters are recognized by utilizing moments to recognize alphabetic character and structure information of numeric character to recognize number.The experiments' results show that the method of locating container codes is effective and the method of character recognition has some reference value.