Studies On Container's Box Number Recognition Based On BP Neural Network

With the development of Information Technology, the image processing and recognizing technology have already applied to a lot of fields , just as traffic control, bank check recognition, cancer cell distinguishing , remote sensing technique, and so on and becomes one of the important technologies having features of the times on the new 21 centuries .Staring from the theory of image processing and recognizing technology, this thesis expatiate the content of research and development about "container's box number recognize system based on BP neural network" detailedly and system handling process: image preprocess, box number area allocation, character segmentation, feature extraction and recognition. Because present algorithms cannot perform the project practice's idiographic request perfectly, therefore bring forward the improved algorithm on varying degrees in each mostly tache about designing. Main work as follows:1. In container's image preprocessing, bring forward use the methods of median sieve combine with remove scatter noise method to cancel the noise.2. In box's number location, according to container's box number character characteristic use the location methods of frequency combine with the prior knowledge of box's number position.3. In box's number recognition, design respectively letter network and digital network to recognize the box's number of letters and digits by BP nerve-network to avoid similar character mix up.Finally apply what be suggested that method, we take an experiment on acquired images with Microsoft Visual C++6.0 platform. The experiment result indicates that using image processing and pattern recognition technique flexibility can recognize container's box number, the recognition rate can be more than 96 percent. It has prospect of practical application.