摘要
洪水预报分析需要输入大量图像,然而纸质水文年鉴逐年磨损老化,传统方法人工投入大、错误率高,因此水文年鉴资料的数字化研究具有重要意义。本文提出基于版面分析的多特征融合数字识别方法,并结合水文年鉴中数值的时间序列相关性提出后期纠错机制来提高识别的正确率。对水文年鉴图像的实验结果表明,该方法具有较高的识别精度,并且能够还原误识结果的真实值。
Flood forecasting analysis requires to input a lot of images. Due to the gradual wearing and aging of paper hydrological yearbooks as well as the high-cost and high error rates of traditional methods, the research on the digitalization of hydrological yearbook data is of a great importance. We propose a digital recognition method with multi-feature fusion based on layout analysis, and provide a post-correction mechanism according to the relevance of time series. For hydrological yearbook pictures, experimental results show that our method achieves high recognition accuracies and is practical to restore the true values of misrecognitions.
出处
《计算机与现代化》
2016年第12期78-82,86,共6页
Computer and Modernization
基金
江苏省重点研发计划项目(BE2015707)
江苏省水利科技资金资助项目(2012034)
关键词
纸质水文年鉴
数字化字符识别
特征融合
时间序列
paper hydrological yearbook
digitization character recognition
feature fusion
time series
