【正文】 low chart shown in Figure 1. Figure 1line character recognition image coding system flowchart Online tire image coding character recognition system requires the production pipeline through the acquisition of each tire with tire encoded image, and then through image processing, coding to extract features of the tire, using the appropriate Image preprocessing Followup treatment FeaExtraction and Identification Code Coded image capture and storage recognition algorithm to identify each coded character. Tire coding characters as a certain deformation in the tires, and different camera angles, are also great differences in the coding images, regularity is poor, so coded image preprocessing and recognition algorithms of selection is very important. 2 Image Acquisition and Storage Line coding monly used digital camera images, digital cameras, digital video cameras capture and processed in puter, the system uses QuickCamPro4000 tire coding digital camera image capture, directly from JPG format. Coded images generally must first convert BMP image format, because the BMP format has bee the de facto standard PC in the field almost all of the Windows operating system designed for image processing software to support this format of the image. BMP is the original Windows bitmap format, which can be used to save any type of digital map data, can support all Windows supported screen resolution and color bination. Under normal circumstances, in order to ensure the display of high efficiency, it does not have any pressed image data, so a small bitmap may occupy considerable space. BMP bitmap file includes the bitmap file header, bitmap information header, palette, bitmap data area of four parts, bitmap file header from 14 bytes constitute the bitmap header from 40 bytes position, tone color palette depends on the number of monochrome color images. Board accounted for 8 bytes, 16color palette images accounted for 64 bytes, 256color palette image 1024 bytes total, 224color images without color palette, the bitmap data from the region under the order of the data by row and on the arrangement from left to right. 3 Preprocessing Image preprocessing includes are: gray image, image noise reduction and enhancement, coding, edge detection, image geometry correction, image coding region of extraction, encoding image binarization, character segmentation, character normalization and so on. Here are some key aspects of the process. gray image processing Images are usually color coded, the actual identification with the image is grayscale, where the need to convert first colorcoded images to grayscale. In the RGB color model, if R = G = B, then color (R, G, B) indicates a Black white color, in which R = G = B is called the value of gray value, gray level processing is to make the color of the R , G, B ponent value equal to the process. Grayscale processing methods are monly used weighted average method, that is, R = G = B = (WRR + WGG + WBB) / 3 Which, WR, WG, WB are the R, G, B the weight of experimental and theoretical proof, when WR = ,