Research Of Image Recognition Method On Financial Invoice Printing Number And Par Value

In financial field, many occasion which needs dealing with plenty of the character information input, will rely on the input of data information greatly. The number on invoice is the identification of invoice printing quantity, each piece of no repetition, therefore it can be used for the identity of invoice identification. Developed an aptitude system by computer vision for Invoice numbers recognition, the number is recognized and recorded with binding by the system, then the organization of the Invoice could be easy. So the automatic register system has utilize tremendous and amplitude application foreground. In this paper, including the automatic recognition system for Invoice numbers, the invoice value is also recognized. And this was built by the technique of image processing and pattern recognition.Firstly, compared the camera of CCD and CIS, a kind of Canon CCD camera was chosen. The image gotten by camera has many noises. Through the experiment of average filter and median filter, the algorithm of Gauss was adopted to dispel the noises.Compared with the prevalence algorithm of segmentation, the experiment result show they are not content the system target in effect, speed and complexity. This paper aims at the important factor that the information in receipt image is red line, make reservation for image red weight handling, then carry out automatic threshold value for invoice image cutting apart. Then the image was processed by iterative method binarization and morphology close operation.The noises was wipe off by calculate the areas and connect the breakpoints. In level location, the gray projection method was adopted. In perpendicular orientation, an improved method of distance of traversing number body was adopted. Then every number has a notable peak, and the two or more peaks made by projection directly is avoided.In recognition algorithm, A new structure-analyzing algorithm was be put forward by calculate the transfer of the number body times. The algorithm is simply and fast enough to content the processing system. Finally, the application of template matching has been introduced.100 sheets of Invoice was randomly chosen, the recognition ratio is 98 percent.