关键词: 集装箱箱号识别, 差分边缘, 最小二乘法, 倾斜校正, BP神经网络

Abstract:

Aiming at the factors such as uneven illumination, deflection and tilt of container number in the image of container number, the key technical problems in character recognition of container number are mainly studied. For the problem of uneven illumination of container number image, an improved rough location method of differential edge detection is adopted. The improved least squares method is used to effectively solve the problem of container number deflection which is difficult to locate accurately. A gradient descending projection character correction and segmentation algorithm is used to realize the correction and segmentation of tilted container number. The BP network is used for character recognition. Experiments on 1?050 images captured under different conditions show that the comprehensive recognition rate of the above algorithm is significantly improved compared with traditional algorithm and depth learning algorithm, and it meets the real-time requirements.

Key words: container code recognition, differential edge, least square method, tilt correction, BP neural network