Secondary segmentation extracted algorithm based on image enhancement for intelligent identification systems
Due to the indefinite position of the characters in the invoice and the difference of the color shades, which greatly increases the difficulty of intelligent identification, it is difficult to meet practical applications. In order to solve this problem, this article proposes a quadratic segmentation...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-12-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147718818737 |
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| _version_ | 1849698972156821504 |
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| author | Heng Dong Ying Jiang Yaping Fan Yu Wang Guan Gui |
| author_facet | Heng Dong Ying Jiang Yaping Fan Yu Wang Guan Gui |
| author_sort | Heng Dong |
| collection | DOAJ |
| description | Due to the indefinite position of the characters in the invoice and the difference of the color shades, which greatly increases the difficulty of intelligent identification, it is difficult to meet practical applications. In order to solve this problem, this article proposes a quadratic segmentation algorithm based on image enhancement. Specifically, we first enhance the color of the image based on gamma transformation, and then separate the machine-printing character from the blank invoice based on the color analysis of the machine-printing character. Then according to the open operation in the image processing field and the bounding rectangle algorithm, the pixel information of the machine-printing character is obtained, which is convenient for getting the character information. The algorithm can achieve effective extraction of machine-printing characters and also reduce the difficulty of invoice identification and improving the accuracy of invoice identification. Simulation results are given to confirm the proposed algorithm. After many experiments, the extraction accuracy of this algorithm is as high as 95%. |
| format | Article |
| id | doaj-art-36666cd96ecb40f99e4163c9b2c69fde |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2018-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-36666cd96ecb40f99e4163c9b2c69fde2025-08-20T03:18:45ZengWileyInternational Journal of Distributed Sensor Networks1550-14772018-12-011410.1177/1550147718818737Secondary segmentation extracted algorithm based on image enhancement for intelligent identification systemsHeng DongYing JiangYaping FanYu WangGuan GuiDue to the indefinite position of the characters in the invoice and the difference of the color shades, which greatly increases the difficulty of intelligent identification, it is difficult to meet practical applications. In order to solve this problem, this article proposes a quadratic segmentation algorithm based on image enhancement. Specifically, we first enhance the color of the image based on gamma transformation, and then separate the machine-printing character from the blank invoice based on the color analysis of the machine-printing character. Then according to the open operation in the image processing field and the bounding rectangle algorithm, the pixel information of the machine-printing character is obtained, which is convenient for getting the character information. The algorithm can achieve effective extraction of machine-printing characters and also reduce the difficulty of invoice identification and improving the accuracy of invoice identification. Simulation results are given to confirm the proposed algorithm. After many experiments, the extraction accuracy of this algorithm is as high as 95%.https://doi.org/10.1177/1550147718818737 |
| spellingShingle | Heng Dong Ying Jiang Yaping Fan Yu Wang Guan Gui Secondary segmentation extracted algorithm based on image enhancement for intelligent identification systems International Journal of Distributed Sensor Networks |
| title | Secondary segmentation extracted algorithm based on image enhancement for intelligent identification systems |
| title_full | Secondary segmentation extracted algorithm based on image enhancement for intelligent identification systems |
| title_fullStr | Secondary segmentation extracted algorithm based on image enhancement for intelligent identification systems |
| title_full_unstemmed | Secondary segmentation extracted algorithm based on image enhancement for intelligent identification systems |
| title_short | Secondary segmentation extracted algorithm based on image enhancement for intelligent identification systems |
| title_sort | secondary segmentation extracted algorithm based on image enhancement for intelligent identification systems |
| url | https://doi.org/10.1177/1550147718818737 |
| work_keys_str_mv | AT hengdong secondarysegmentationextractedalgorithmbasedonimageenhancementforintelligentidentificationsystems AT yingjiang secondarysegmentationextractedalgorithmbasedonimageenhancementforintelligentidentificationsystems AT yapingfan secondarysegmentationextractedalgorithmbasedonimageenhancementforintelligentidentificationsystems AT yuwang secondarysegmentationextractedalgorithmbasedonimageenhancementforintelligentidentificationsystems AT guangui secondarysegmentationextractedalgorithmbasedonimageenhancementforintelligentidentificationsystems |