摘要
在详细分析电煤图像及其对应的煤质指标数据的基础上,针对当前煤质指标检测工具时效性差的问题,提出一种基于电煤图像数据分析的煤质指标检测方法。利用图像识别技术对煤质指标进行快捷检测,分为电煤图像预处理、图像特征提取与选择和分类决策3部分。实验结果表明,该检测方法是可行的,选择颜色直方图和Tamura纹理特征综合进行煤质指标检测具有较高准确率。
On the basis of a detailed analysis of coal images and its corresponding coal quality index,the method of coal quality index detection based on big data analyses of coal images was proposed.Image recognition technology was used and coal image preprocessing,image feature extraction and selection and classification decision were included.Experimental results show that the proposed method is feasible,and selecting color histogram and Tamura texture feature to test coal quality index has higher accuracy rate.
出处
《计算机工程与设计》
北大核心
2016年第1期163-168,共6页
Computer Engineering and Design
基金
国家自然科学基金项目(61272109)
武汉市应用基础研究计划基金项目(2014010101010027)
关键词
煤质指标检测
图像识别
图像处理
特征提取
分类决策
coal quality index testing
image recognition
image processing
feature extraction
classification decision
