A System to Localize and Recognize Texts in Oriented ID Card Images

ID card recognition is an application scenario in image recognition. As an important identity certificate for citizens, ID card identification and information management has also become a hot issue of concern. Chinese ID card images recognition mainly faces the following problems: Firstly, the shadow grid lines and the noise interference caused by the camera hardware conditions and illumination, together with the useful information in the picture, cause a huge problem of extracting useful information in the ID card. Secondly, the way to extract the foreground part in a complex context is also important for recognition. In response to these problems, this paper proposes an ID card region location method based on face detection and national emblem detection. This method can locate the foreground target area of the ID card in a complex context. In addition, the method of rotation correction of ID card region based on Hough transform is proposed, which can correct the tilt target within the range of tilt angle less than 45 degrees. In the text localization stage, the morphological method of the image is used to locate the text area. The deep convolutional neural network is then used to implement character segmentation and recognition. The recognition process proposed in this paper achieves a better recognition effect, and the recognition of Chinese and digital characters reaches 99.7% recognition rate, and can cope with the rotation tilt and the image containing the background.