CAPTCHA recognition based on image recognition and neural networks

Based on image recognition and neural networks (NNs), a rapid and effective CAPTCHA recognition method was proposed which has different characters of numbers and English letters. Firstly, pre-operating was put in practice, including graying, binaryzation and removing noise to get the binary image with higher quality. Secondly, images with single character were acquired through an improved segmentation algorithm combining connected domain and projection together, and then normalized. Thirdly, features of character image samples were extracted; the NNs were built and trained. Finally, the trained NNs were tested to realize character recognition. Based on the software environment of Matlab, the recognition processing and result of many CAPTCHA images from different websites were proposed. The experiments show that the method is effective and feasible for the CAPTCHAs which contain irregular placed characters and much noise.