In order to achieve the real-time detection of Coding characters in the process of filling cans, a real-time detection method based on convolutional neural network is proposed. This method initially adopts the histogram equalization and OSTU to deal with the images and then operates the images by the morphological inflation method. Besides, the region of the printed code characters is extracted by the area method of connected domain and then rotates and corrects this region. By using the projection method, the region is divided into single characters which will be trained by the convolutional neural network under the offline state. All above procedures are done in order to recognize the characters while doing the online detection. Experiments show that the average time of every detected image is 46 ms and its accuracy achieves 98.97% which show high instantaneity and accuracy. Thus, it can meet the demand of the real-time detection of industrial cans characters.