Technique Research Of The Second ID Card's Character Identification Based On Image Analysis

Image character identification is an important field of application in image processing and Pattern Recognition theory, and it is the major way of realizing intelligent human-computer communication. In recent dozens of years, they are extensively researched. Character identification is an important part of Pattern Recognition, and it has main useful value and theory significance in information processing, office automation, post system, bank system.At the present time, OCR(Optical Character Recognition)character identification's technique has already relatively matured, but the error rate of conglutination character identification is rather high. Generally speaking, the main reason is that the error syncopate of the conglutination character can lead to character's severity distortion deformation, so correct identification can't be obtained, therefore syncopate of conglutination character identification become a key technique to improve identification rate. Existing syncopate methods are: (1)the direct syncopate method based image analysis: the reasonable syncopate point among the characters is looked for through image analysis, but the error of syncopate is rather high; (2)the syncopate method based identification: several possible syncopate points are determined through image analysis, and reasonable syncopate point is chose by means of the result of identification. The latter syncopate method's identification is higher than the first one, but it needs to be identified many times, the step is verbose and time-consuming.To improve the identification rate of conglutination character and the speed of identification, this thesis's main research and innovations are divided into two parts:First, aiming at the algorithm of the second generation ID card's character identification, three points are included: (l)The method of segmentation which is adequate for extracting interested areas of the second generation ID card(The third chapter), to realize location and segmentation of characters, the real character image is segmented from complicated background of ID card, and some unessential signal are disposed according to certain norm, and the size of characters is normalized , position and font-weight of stroke, and certain identification principle is used to classify the character, its property is determined; (2) The character syncopate method of the second generation ID card: to reduce conglutination rate of syncopate character, and aiming at stain, fade, asymmetrical illumination and rather low resolution which can effect detection region's conglutination character, up and down profile concavo-convex feature are adopted to approximately detect single character's width, the restrict condition of character's width is used to directly set up syncopate path according to profile concavo-convex feature, so the correct rate of character identification can be improved; (3) Aiming at the second generation ID card's character identification, a method which is put forward to detect character string's profile. Feature is firstly extracted from image character region in this method(The fifth chapter), after the areas of character are gained, and then fluctuation profile concavo-convex character is adopted to approximately detect single character's width, and the steady local character is accordingly chose, and frame sentence identification is used to identify the character.Second, software prototype is designed to achieve the second generation ID card's identification system(The sixth chapter), three parts are divided by character identification system: (1)Pretreatment module: algorithm is adopted in this module in the thesis, the image is stretched by gray, and then the image is filtered by the method of space domain, which is based on gray stretching, and the method of character segmentation is adopted in the third chapter in this thesis. (2)Features extracted module: up and down profile concavo-convex feature is adopted to approximately detect single character's width, the character is extracted under the restrict condition of character's width and according to profile concavo-convex feature. (3)Character identification module: a method which combines structure feature of character profile with statistics feature is adopted, and the characters from character library are divided into texture image and non-texture image, and then the texture image and non-texture image are matched by region, so the purpose of matching is achieved.