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Research on PDF417 Barcode Recognition Method

Author: LiuFaYao
Tutor: YinJianPing
School: National University of Defense Science and Technology
Course: Computer Science and Technology
Keywords: PDF417 Distorted barcode Mathematical Morphology Edge Detection Canny Projection Waveform analysis
CLC: TP391.44
Type: Master's thesis
Year: 2010
Downloads: 91
Quote: 1
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Abstract


Bar code as a means to an information storage and dissemination of information, widely used in various fields of social production and life. In recent years the concept of things heating up, bring new opportunities to the development of barcode technology. The traditional one-dimensional bar code can not meet the application requirements due to capacity constraints, and a variety of two-dimensional bar code came into being. PDF417 barcode information capacity, a wide range of information coding, decoding the reliability of the many advantages to users of all ages, has been widely used in the industry. Commercially available PDF417 barcode reader, or technology by foreign monopoly, or the barcode recognition only under ideal conditions. For a variety of complex situations, such as high noise, the PDF417 barcode recognition distorted, low-contrast conditions, there are many research issues. From the the PDF417 barcode shape, texture features and encoding rules, error correction principle-depth study of the the barcode positioning recognition problems in a variety of complex cases. The main innovation of this paper work is summarized as follows: 1, for a variety of complex conditions, such as background noise, low contrast and uneven illumination PDF417 barcode recognition rate in the case of a detection based on mathematical morphology and edge The barcode positioning method (MMED). The method first preprocessing of the input image, and then through the edge detection and mathematical morphology operation discrete barcode region expands into a region of China Unicom, detecting the outline of a rectangle in order to achieve a coarse positioning; then line scanning strategy, the pattern search and regional The precise treatment positioning the PDF417 barcode four vertices. The experimental results show that the method is robust and able to solve a variety of complex cases barcode positioning. Distorted barcode image difficult to locate hard to identify the problem, presents a distorted barcode positioning method. MMED-based positioning method, the method by pretreatment extraction the convex quadrilateral contour, and improved mode search strategy, the precise positioning of the code area to distort the positioning of the bar code; raised concept of barcode rectangular degrees rotational deformation, and to distinguish between the plane of the bar code space rotation deformation, the deformation of the bar code for the plane rotation using affine transformation inverse rotation corresponding angle correction, the barcode deformation space rotation perspective transformation and bilinear interpolation methods to correct. The experimental results show that the proposed method can effectively identify and correct various distortions barcode image and has high real-time. 3, for the problems of traditional segmentation method based on the projection of ranks Sobel edge detection, segmentation algorithm based on the projection and waveform analysis of barcode ranks. Column segmentation algorithm based on the characteristics of PDF417 barcode column boundary projection of the number of vertical direction black spots threshold segmentation, extraction peak then equidistant testing, to eliminate noise points, to achieve a column boundary point extraction; For line segmentation, First line differential statistics, filtering and processing, by extracting the peak line split. Experimental results show the effectiveness of the algorithm. 4, a PDF417 bar code recognition system was designed and implemented. The system is modular in structure design, with good scalability; implemented based on the OpenCV library with high real-time.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Optical pattern recognition devices
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