Research on Optimization of CAPTCHA Recognition Algorithm Based on SVM

Image verification code is the main mode of security verification in current network applications. The identification efficiency of verification code is a difficult problem that affects network data crawling, which has realistic research significance and value. This paper proposed an SVM (Support Vector Machine)-based recognition method. On the basis of fully analyzing the existing SVM recognition mechanism process, the image is first binarized and filtered for character image preprocessing, then feature extraction, and then classification model is established for recognition. It is proved that this method can achieve fast and accurate results by training and comparing characters in many categories such as adhesion and rotation.