An Intelligent Knowledge Extraction Framework for Recognizing Identification Information from Real-World ID Card Images

In this work, we study the problem of recognizing identification (ID) information from unconstrained real-world images of ID card, which has extensively applied in practical scenarios. Nonetheless, manual ways of processing the task are impractical due to the unaffordable cost of labor and time consumption as well as the unreliable quality of manual labeling. In this paper, we propose an intelligent framework for automatically recognizing ID information from images of the ID cards. Specifically, we first conduct marginal detection using a multi-operator algorithm and then localize the region of ID card from all the proposed candidate regions with SVM classifier. Furthermore, we segment linguistic characters from the card region by an improved projection algorithm. Finally, we recognize the specific characters by an eight-layer convolutional neural network. We perform extensive experiments on a Chinese ID card dataset to validate the effectiveness and efficiency of our proposed method. The experimental results demonstrate the superiority of proposal over other existing schemes.