The Research And Application Of Image Denoising Method Based On Edge Detection On The Recognition Of Two-Dimension Barcode

Barcode technology is a sort of automatic identification technology progressed with the development of computer applications.And it has been widely applied in the society with its characteristics such as rapidity,accuracy,low-cost,good ability to protect from forgery and so on.But for barcode image,in the process of collection,acquisition,encoding and transmission,all the barcode images will be polluted by the visible or invisible noise to different extent.When applying traditional methods to denoise the barcode image, although it can effectively remove the noise in the image,it can not retain the image edge information well.Accordingly,it will affect the recognition rate of the barcode.To this situation above,this paper proposes a sort of wavelet thresholding denoising method based on GCV(Generalized Cross Validation) rule and edge detection.The edge information of the barcode image will be retained while being denoised,it will consider denoising and retaining the edge information of the barcode altogether.It is unnecessary to worry about the loss of the edge information of barcode while being denoised.Practice has proved that this denoising method can improve the PSNR(peak signal to noise ratio).First of all,this paper introduces QR Code and then introduces a variety of wavelet thresholding denoising methods.After that,the wavelet thresholding denoising method based on GCV rule is discussed in detail,and the advantage of this method is interpreted.Then it is proved that the advantage of this denoising method based on edge detection comparing to the straightforward denoising method does exist.After that,the recognition system is designed and the main flow of the barcode recognition is interpreted.Finally,the experimental results show that the method can acquire satisfactory effect to a certain extent when we apply this method in the system platform.