Working condition recognition based on an improved NGLDM and interval data-based classifier for the antimony roughing process
详细信息 查看全文
- 作者：Xia Peng ; Tao Peng ; pandtao@163.com" class="auth_mail" title="E-mail the corresponding author ; Lin Zhao ; Yanpo Song ; Weihua Gui
- 关键词：Working condition recognition ; Improved NGLDM ; Composite texture ; Interval data ; SVM ; Antimony roughing
- 刊名：Minerals Engineering
- 出版年：2016
- 出版时间：February 2016
- 年：2016
- 卷：86
- 期：Complete
- 页码：1-9
- 全文大小：2113 K
文摘
- •
An improved NGLDM is presented for an image.
- •
Defined a new texture feature of image namely composite texture.
- •
Combined with the ore grade, the numerical intervals representing the extracted composite textures are adopted for off-line classification and on-line recognition by a support vector machine (SVM) classifier for froth images.
- •
The improved NGLDM could reflect the texture of froth surface more completely.
- •
The composite texture has better accuracy in classification than traditional one.