| Pattern Recognition technology is a significant branch of signal processing and artificial intelligence, which is also a main research and application field of current high-tech. Optical character recognition is the principal technology of computer intelligence man-machine interface. Number character recognition as a research branch of optical character recognition has very profound academic meaning and comprehensive application value in practice. The recognition technology consists of pattern recognition, image processing, artificial intelligence, communication theory, computer science, and so on. It, which is also relative to psychology, is a general technology.The arithmetic in this paper is used for detecting the second version ID card number in the course of ID card manufacturing and satisfies the real-time and accurate requirements. The accomplished work in this paper mainly include ID card image segmentation, ID card number image segmentation, pretreatment of ID card number image, the division of single number image, the number image filter and smoothness, Hildtch skelecton arithmetic's modification, the definition and extraction of the feature points and the number recognition.ID card image segmentation is the premise of ID card number recognition. Whether ID card image is cut exactly is relative to ID card number recognition, and it directly influence the ratio of rejected recognition. Here, we cut the ID card image by dint of detecting the ID card boundary lines. Firstly, we sample some points and construct an optimal line through these sample points as much as possible. The line is just the boundary of ID card image. In the same time of detecting the four lines, we can make certain whether the ID card is inclined or not. And if the card is badly inclined, we can revise it immediately. By succession, we can get the rough location of the ID number block according to the whole structure of ID card, and we can estimate if there are 18 numbers in the interesting region. If there are 18 numbers in the region, we continue to recognize the numbers. If not, we will detect the ID card image again. During the course of getting ID card number image, we must consider the following instances, such as whether the ID card is reverse and whether the ID card image is a mirror image, and so on.The segmentation of ID card number image is also absolutely necessary to ID card number recognition. Firstly, we adopt a self-adaptive binary image method to process the different gray level images. Following this, we make the binary image vertical projection and horizontal projection. The detailed steps are as follows: Suppose that there are two vectors which are a vertical vector and a horizontal vector, one's size is the Width of the image and the other's size is the height of the image. In succession, we scan the whole image, if the scanned point is number point, the relative location of both the vertical vector and the horizontal vector add one, and otherwise, both the vertical vector and the horizontal vector keep invariable. After scanning the whole image, we can take two projection curves and the eighteen ID numbers can be got through computing the boundary points of the local support sets in the two curves. Thus we can process and recognize the eighteen numbers digital images.We need to filter the eighteen numbers in ID card binary image that we have gotten. Here, we consider the information of both the number's width and the curvilinear directory of the number and then adopt the Gabor filter to process the images. The image that has been filtered is comparatively smooth. Thus, we can get much better skelecton images through these smooth binary images.Most of number character information is focus on the skeleton image, so we can get the character information easily on the skeleton images. It makes the arithmetic simple and the run-speed rapid by a long way. The character information used for recognizing the number includes end-points and trifurcate points, and we can distinguish the different... |
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