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字符切分

字符切分的相关文献在1997年到2022年内共计115篇,主要集中在自动化技术、计算机技术、无线电电子学、电信技术、公路运输 等领域,其中期刊论文67篇、会议论文3篇、专利文献683942篇;相关期刊41种,包括逻辑学研究、河北省科学院学报、沈阳建筑大学学报(自然科学版)等; 相关会议3种,包括第十一届全国多媒体技术学术会议、第二届全国信息获取与处理学术会议、2008年中国信息技术与应用学术论坛等;字符切分的相关文献由240位作者贡献,包括丁晓青、刘长松、彭良瑞等。

字符切分—发文量

期刊论文>

论文:67 占比:0.01%

会议论文>

论文:3 占比:0.00%

专利文献>

论文:683942 占比:99.99%

总计:684012篇

字符切分—发文趋势图

字符切分

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  • 丁晓青
  • 刘长松
  • 彭良瑞
  • 卢朝阳
  • 安艳辉
  • 李静
  • 董五洲
  • 钟辉
  • 阿地力·依米提
  • 亓文法
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    • 刘星辰; 金小峰
    • 摘要: 为解决朝鲜语古籍数字化中朝汉文种混排字符切分困难的问题,提出一种朝鲜语古籍图像的文字切分算法.针对古籍列与列之间存在不连续间隔线、倾斜或者粘连等问题,提出一种基于连通域投影的列切分方法.利用连通域的删除、合并、拆分等操作对文字进行切分.使用一种多步切分法完成了具有文字大小不一,横向、纵向混合排版特点图像的字符切分工作.对于粘连字,采用改进的滴水算法进行有效切分.实验结果表明所提出的算法能够很好地完成朝、汉文种混排,文字大小不一,排版情况复杂的朝鲜语古籍图像的文字切分工作.该算法的列切分准确率为97.69%,字切分准确率为87.79%.
    • 陈习; 曾智翔; 张蓓蕾; 陈春
    • 摘要: 本论文基于图像预处理的研究,在图像的字符分割提取前,增加图片整体分割提取的步骤,设计出一种基于字符切分的识别字符排版的方法.该方法符合实际电力铭牌文字排版多样化的需求.通过字符的排版识别,可以让一份完整铭牌切分成多个字符排版一致、样式统一的部分.这里以电力铭牌的识别实验为例,其结果也验证了本文提出方法的有效性,相比于传统的文字解析算法有比较好的准确度.
    • 姑丽祖热·吐尔逊; 尤努斯·艾沙; 吐尔根·依布拉音; 库尔班·吾布力
    • 摘要: 为提高文档图像字符的可读性和切分与识别的准确率,对印刷体维吾尔文文档图像进行研究,尤其是对连通段切分和字符切分等难点问题提出分割方法。使用跑长码的连通区域算法,结合重叠度计算方法,进行连通段切分;基于维吾尔文字符在基线上相接的特点,在基线位置估计的基础上,找出字符的切点。切分结果表明,该算法比其它算法切分结果效果更好。%To improve the accuracy of Uighur character recognition,a study was carried out on the Uighur printed document image,especially for the connected component segmentation and character segmentation which have now become the most difficult problems,an efficient segmentation method was proposed.Long run code connected regions algorithm and overlapping calculation methods were combined to segment the words on the document image.Uighur characters were connected in the base-line.Based on this characteristic,the baseline of the each word was estimated,and the segmentation positions of characters were found out.The results indicate better segmentation results than the algorithm proposed earlier.
    • 焦圣喜; 刘鲁生; 张彬
    • 摘要: 字符切分是字符识别系统中的一个重要环节。粘连普遍存在于手写和低质量印刷文本图像中,是指字符图像中有笔画搭接的情况。对于粘连字符,普通切分算法很难处理。介绍了几种针对粘连字符的切分算法,在介绍算法流程的基础上,对该种算法的优缺点以及粘连字符的发展方向进行了探讨。
    • 谢兰军; 刘健
    • 摘要: The purpose of character segmentation is to cut out entire character string and turn it into a single digital image.Character segmentation is one of the key steps in the digital character recognition.After preprocessing,due to adhesions caused by a decimal point, character segmentation cannot be done correctly.In order to solve the problem of adhesions by decimal, proposing a method by excluding small areas to remove the decimal point.First,we get the statistical area of the various parts of the image,and then determine the threshold to distinguish the decimal from numeric characters,finally exclude the decimal point.After that,we preprocess the image,use linear projection segmentation to pick out the character.The experiment indiclrte that the method works well.%字符切分的任务是把整个字符串图像中的每个字符切割出来,使其成为单个数字的图像。字符切分是数字字符识别中的关键步骤之一。在图像预处理后,由于小数点粘连造成字符粘连,无法正确切分字符。针对小数点造成的粘连情况,考虑小面积剔除法将小数点去除,保证字符切分正常。小面积剔除法首先将图像中各个部分加以统计得到其面积,然后根据面积的不同确定阈值将小数点与数字字符区分开来,剔除小数点。经过处理之后的图像再进行预处理,使用直线投影切分法将字符切分提取出来。实验表明该方法效果良好。
    • 张振东; 哈力旦·阿布都热依木; 赵永霄
    • 摘要: To research and develop the webcam taking and translating Uighur word system and to solve the difficulties of Uighur word letter segmentation in the system ,a new algorithm based on the adaptive threshold was proposed .Aiming at the features of the Uighur word pictures taken by the webcam ,the word was exacted accurately first .Then the main part of the word was used to make the projection histogram of pixels ,the threshold of segmentation was extracted automatically .The threshold was used in segmentation at last .Experiments verify the segmentation accuracy rate of this method reaches over 96% .At the same time ,it has better adaptability for different images ,and it can promote the study of Uighur word camera translation system .%为研究开发维吾尔文摄像头取词翻译系统,解决其中维吾尔文字单词图像切分难题,提出一种印刷体维吾尔文字符自适应切分算法。针对摄像头取词图像特点,准确提取目标单词;利用维吾尔文单词基线以上的主体部分做像素积分投影,从投影结果中自动提取切分阈值;利用该阈值完成字符切分,达到自适应的效果。经过实验验证,该方法切分正确率达到了96%以上,针对不同图像具有较好的适应性,对维吾尔文摄像头取词翻译系统的研究具有促进作用。
    • 王景中; 朱其猛
    • 摘要: Aiming at the problems of the judgment of inverted text image excessively relied on the punctuation and the text accuracy of judgment was not ideal,a new inversion judgment algorithm for Chinese text images is proposed. This algorithm makes full use of the outline of stroke and the characteristics of Chinese characters,on the basis of the left strokes founded by the software,using a particular al-gorithm to determine the direction of the text. The algorithm solves the problems above properly,at the same time,it has good effect for inversion judgment of distorted text image. The experimental results also verify the feasibility and effectiveness of this method. Compared with the existing inverted judgment algorithm,this method not only has more universal significance,efficiency and accuracy has also been largely increased.%针对目前对文本图像倒置判断过分依赖文本标点的局限以及判断准确率不理想的问题,提出了一种新的中文文本图像倒置判断算法。算法运用投影法,对汉字进行定位,充分利用汉字笔画连续属性以及动态搜寻路径寻找撇笔迹,最后根据撇笔画的轮廓与走向特征运用特定的策略与算法判定出文本的方向。此法不仅很好地解决了上述问题,同时对扭曲的文本图像的倒置判断也有良好的效果。实验结果也验证了此法的可行性与有效性。通过实验结果与现有倒置判断算法相比,此法更具普遍适用性,在效率和准确率上也得到了较大的提高。
    • 杨义军; 洪汉玉; 章秀华; 王逸文; 俞喆俊
    • 摘要: To meet the demand of tracking each billet in the heavy rail production line, a billet character recognition algorithm based on computer vision was proposed. Firstly, multistage segmentation filtering based on OTSU and clustering processing was adopted to locate the billet character precisely. Secondly, the segmentation algorithm based on intelligent multi-agent was used to divide the billet character accurately. Lastly, the multilevel recognition algorithm incorporation the template matching and feature recognition was used to recognize billet character correctly. The experimental results show that the proposed algorithm in this paper can recognize the billet character correctly and quickly.%针对重轨生产线钢坯支支跟踪的需求,研究了一种基于计算机视觉的钢坯字符识别方法.该识别方法对在线采集到的钢坯字符图像采用基于最大类间方差的多级分割滤波与聚类处理突出字符目标区域,从而精准定位出钢坯字符;采用基于智能多代理者的切分算法来完成钢坯字符的精确切分;采用模板匹配与结构特征识别相结合的多级识别方法来正确识别出钢坯字符.实验结果表明所提出的算法能正确快速地识别出钢坯号字符.
    • 洪汉玉; 杨义军; 章秀华; 颜露新; 张天序
    • 摘要: In the process of billet detection and recognition, how to accurately divide the characters at ends of steel in the complex scene is a highly complicated intelligence problem. In order to solve this complex problem, a segmentation algorithm based on intelligent multi-agent is proposed in this paper. The algorithm takes these functions: the segmentation of characters, the combination of regions, the division of regions and the calculation of features, as the agents in the subordinate control layer. And then, these agents work in coordination with each other in the control of the master agent. Moreover, the segmentation information is fed back to the master agent to control and analyze the agents. At last, the billet characters are divided accurately through the proposed algorithm of intelligent multi-agent. The segmentation experimental results show that the proposed algorithm divides the billet characters in the complex scene accurately and steadily. What's more, the algorithm solves the difficult problem of the accurate segmentation of billet characters in the complex scene, and provides the guarantee for the characters recognition.%在生产线钢坯检测识别过程中,如何准确地切分生产线实际复杂场景下的钢坯端面字符是一个高度复杂的智能问题.为了解决这一复杂问题,本文提出了一种基于智能多代理者的字符切分处理方法,将分控制层中的字符区域分割与切分、区域合并、区域分裂、特征计算等功能子程序作为个体代理者,主控制层作为主控代理者对这些个体代理者根据具体需要进行统一分工协调,同时各子代理者的切分信息反馈给主控代理者作为分析、控制各子代理者的重要因素,进而完成钢坯号字符的精确切分.实验结果表明,本文提出的算法能对复杂场景中的钢坯字符完成精确的切分,具有良好的稳定性与准确性,解决了复杂场景中的钢坯字符准确切分的问题,为后续钢坯字符的识别提供了保证.
    • 王彩玲; 高倩
    • 摘要: The intelligent traffic is the main direction of the development of the current traffic management, The automatic li⁃cense plate recognition system is the core of the intelligent traffic. In order to improve the performance of automatic license plate recognition system, Designed a complex environment with a strong robustness of license plate recognition process, And VC + +based development of its experimental models and the practical application of the model.. Tests show actual video, The system has been basically reached the industry requirements, Has better practicability.%  智能交通是当前交通管理发展的主要方向,而车牌自动识别系统则是智能交通的核心。为了提高车牌自动识别系统的性能,设计了一种在复杂环境下具备较强鲁棒性的车牌识别流程,并基于VC++开发出其实验模型和实际应用模型。实际视频的测试表明,该系统已经基本达到了行业要求,具有较好的实用性。
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