基于数字图像处理的煤矸石数据自动注释方法

Junpeng Zhou, Yongcun Guo
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引用次数: 0

摘要

:提出了一种基于 X 射线采集的煤矸石图像数据自动标注方法。首先,将人工筛选的煤和矸石送入 X 射线采集设备进行图像采样。其次,根据煤炭和矸石图像纯背景的特征,使用灰色阈值进行检测。然后,利用掩膜对检测到的前景物体进行净化,得到单个物体图像。同时,对人工筛选出的煤/矸石进行采样,并同时获取当前检测到的物体的类别信息,建立单体样本数据库。最后,根据建立的单体样本库,在样本库中随机抽取单体,组合生成具有分类和定位功能的样本图像。即完成了煤矸石数据的自动标注。结果表明,通过数字图像处理对煤矸石图像数据进行自动标注的方法能对采集到的煤矸石图像数据进行有效标注,样本生成率高,标注准确率达 99%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Annotation Method of Gangue Data Based on Digital Image Processing
: An automatic annotation method of coal gangue image data based on X-ray acquisition is proposed. Firstly, the manually screened coal and gangue are sent to the X-ray acquisition device for image sampling. Secondly, according to the characteristics of the pure background of coal and gangue images, a gray threshold is used to detect. Further, the mask is used to purify the detected foreground objects, which obtain a single object image. At the same time, the manually screened coal/gangue is sampled and the category information of the currently detected objects is obtained at the same time, and the monomer sample database is established. Finally, based on the monomer sample library established, the monomers randomly were selected in the sample library and combined to generate sample images with classification and location. That is, the automatic annotation of coal gangue data is completed. The results show that the automatic annotation method of coal gangue image data through digital image processing can effectively annotate the collected coal gangue image data, with a high sample generation rate and annotation accuracy of 99%.
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