• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Artificial Organs >Complexity Analysis Based on Image-Processing Method and Pixelized Recognition of Chinese Characters Using Simulated Prosthetic Vision
【24h】

Complexity Analysis Based on Image-Processing Method and Pixelized Recognition of Chinese Characters Using Simulated Prosthetic Vision

机译：基于图像处理方法和模拟假视觉的汉字像素化识别的复杂度分析

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The influence of complexity and minimum resolution necessary for recognition of pixelized Chinese characters (CCs) was investigated by using simulated prosthetic vision. An image-processing method was used to evaluate the complexity of CCs, which is defined as the frequency of black pixels and analyzed by black pixel statistic complexity algorithm. A total of 631 most commonly used CCs that can deliver 80% of the information in Chinese daily reading were chosen as the testing database in order to avoid the negative effect due to illegibility and incognizance. CCs in Hei font style were captured as images and pixelized as 6 × 6, 8 × 8, 10 × 10, and 12 × 12 pixel arrays with square dots. Recognition accuracy of CCs with different complexity and different numbers of pixel arrays was tested by using simulated prosthetic vision. The results indicate that both pixel array number and complexity have significant impact on pixelized reading of CCs. Recognition accuracy of pixelized CCs drops with the increase of complexity and the decrease of pixel number. More than 80% of CCs with any complexity can be recognized correctly; 10 × 10 pixel array can sufficiently provide pixelized reading of CCs for visual prosthesis. Pixelized reading of CCs with low resolution is possible only for characters with low complexity (complexity less than 0.16 for a 6 × 6 pixel array and less than 0.24 for an 8 × 8 pixel array).
机译：通过使用模拟假肢视觉研究了识别像素化汉字（CC）所需的复杂性和最低分辨率的影响。采用图像处理的方法评估CC的复杂度，定义为黑色像素的频率，并通过黑色像素统计复杂度算法进行分析。选择了总共631个最常用的CC，这些CC可以提供80％的中文日常阅读信息，以此作为测试数据库，以避免由于难以辨认和隐瞒而产生的负面影响。 Hei字体样式的CC被捕获为图像并像素化为6×6、8×8、10×10和12×12的带有正方形点的像素阵列。通过模拟假肢视觉测试了具有不同复杂度和不同像素阵列数目的CC的识别精度。结果表明，像素阵列的数量和复杂度都对CC的像素化读取产生重大影响。像素化CC的识别精度随着复杂度的增加和像素数的减少而下降。可以正确识别超过80％的具有复杂性的CC； 10×10像素阵列可以为视觉假体充分提供CC的像素化读取。低分辨率CC的像素化读取仅适用于复杂度较低的字符（对于6×6像素阵列，复杂度小于0.16；对于8×8像素阵列，复杂度小于0.24）。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号