激光与光电子学进展, 2018, 55 (12): 121504, 网络出版: 2019-08-01   

基于离散余弦变换特征和隐马尔科夫模型的铜熔炼过程烟雾分级 下载: 939次

Smoke Classification in Copper Smelting Process Based on Discrete Cosine Transform Features and Hidden Markov Model
作者单位
1 西安工程大学电子信息学院, 陕西 西安 710048
2 中南大学信息科学与工程学院, 湖南 长沙 410083
3 浙江大学控制科学与工程学院, 浙江 杭州 310027
引用该论文

张宏伟, 张凌婕, 袁小锋, 宋执环. 基于离散余弦变换特征和隐马尔科夫模型的铜熔炼过程烟雾分级[J]. 激光与光电子学进展, 2018, 55(12): 121504.

Hongwei Zhang, Lingjie Zhang, Xiaofeng Yuan, Zhihuan Song. Smoke Classification in Copper Smelting Process Based on Discrete Cosine Transform Features and Hidden Markov Model[J]. Laser & Optoelectronics Progress, 2018, 55(12): 121504.

参考文献

[1] Zhang H, Ge Z, Ye L, et al. Vision-based fan speed control system in the copper scraps smelting process[J]. Asian Journal of Control, 2014, 17(5): 1742-1755.

[2] Russ J C. Image analysis of foods[J]. Journal of Food Science, 2015, 80(9): E1974-E1987.

[3] Qin J W, Chao K L, Kim M S. et al. Hyperspectral and multispectral imaging for evaluating food safety and quality[J]. Journal of Food Engineering, 2013, 118(2): 157-171.

[4] Jing J F, Liu S M, Li P F. et al. The fabric defect detection based on CIE L *a *b * color space using 2-D Gabor filter [J]. The Journal of the Textile Institute, 2016, 107(10): 1305-1313.

[5] Schneider D, Holtermann T, Merhof D. A traverse inspection system for high precision visual on-loom fabric defect detection[J]. Machine Vision and Applications, 2014, 25(6): 1585-1599.

[6] Lei N, Soshi M. Vision-based system for chatter identification and process optimization in high-speed milling[J]. International Journal of Advanced Manufacturing Technology, 2017, 89: 2757-2769.

[7] Li X Q, Wang L H, Cai N X. Machine-vision-based surface finish inspection for cutting tool replacement in production[J]. International Journal of Production Research, 2004, 42(11): 2279-2287.

[8] Zhang H W, Ge Z Q, Yuan X F, et al. Rapid vision-based system for secondary copper content estimation[J]. Transactions of Nonferrous Metals Society of China, 2014, 24(8): 2665-2676.

[9] Huang H, Hu X T, Zhao Y. et al. Modeling task fMRI data via deep convolutional autoencoder[J]. IEEE Transactions on Medical Imaging, 2018, 37(7): 1551-1561.

[10] 王苏恺, 潘晋孝, 陈平. 基于结构连续先验的CT图像序列自适应分割算法[J]. 激光与光电子学进展, 2016, 53(11): 111006.

    Wang S K, Pan J X, Chen P. Adaptive segmentation algorithm for CT image sequence based on structure continuity as prior information[J]. Laser & Optoelectronics Progress, 2016, 53(11): 111006.

[11] Blaschke T. Object based image analysis for remote sensing[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2010, 65(1): 2-16.

[12] Lorente D, Aleixos N, Gómez-Sanchis J, et al. Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment[J]. Food and Bioprocess Technology, 2012, 5(4): 1121-1142.

[13] 朱炳斐, 陈文建, 李武森. 基于Fourier-Mellin变换的液晶显示屏显示缺陷检测[J]. 激光与光电子学进展, 2017, 54(12): 121502.

    Zhu B F, Chen W J, Li W S. Liquid crystal display defect detection based on Fourier-Mellin transform[J]. Laser & Optoelectronics Progress, 2017, 54(12): 121502.

[14] Kim CW, Kim HG, Suk H G. A study on the composition determination of Cu alloys by image processing technology[J]. Solid State Phenomena, 2006, 116/117: 795- 798.

[15] Appana D K, Islam R, Khan S A, et al. A video-based smoke detection using smoke flow pattern and spatial-temporal energy analyses for alarm systems[J]. Information Sciences, 2017, 418: 91-101.

[16] Mredhula L, Dorairangaswamy M A. Image denoising using principal component analysis (PCA) and pixel surge model (PSM)[J]. International Journal of Signal and Imaging Systems Engineering, 2016, 9(4/5): 311-319.

[17] Naidu V P S, Raol J R. Pixel-level image fusion using wavelets and principal component analysis[J]. Defence Science Journal, 2008, 58(3): 338-352.

[18] Hanbay K, Talu M F, Ozguven O F. Real time fabric defect detection by using Fourier transform[J]. Journal of the Faculty of Engineering and Architecture of Gazi University, 2017, 32(1): 151-158.

[19] Lin Z C, He J F, Tang X O. et al. Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis[J]. Pattern Recognition, 2009, 42(11): 2492-2501.

[20] Hernandez J R, Amado M, Perez-Gonzalez F. DCT-domain watermarking techniques for still images: detector performance analysis and a new structure[J]. IEEE Transactions on Image Processing, 2000, 9(1): 55-68.

[21] 尹洪涛, 付平, 沙学军. 基于DCT和线性判别分析的人脸识别[J]. 电子学报, 2009, 37(10): 2211-2214.

    Yin H T, Fu P, Sha X J. Face recognition based on DCT and LDA[J]. Acta Electronica Sinica, 2009, 37(10): 2211-2214.

[22] Bicego M, Murino V. FigueiredoM A T. A sequential pruning strategy for the selection of the number of states in hidden Markov models[J]. Pattern Recognition Letters, 2003, 24: 1395-1407.

[23] 陆兵, 顾苏杭. 基于隐马尔可夫模型和分块特征匹配的目标跟踪算法[J]. 激光与光电子学进展, 2017, 54(9): 091006.

    Lu B, Gu S H. Object tracking algorithm based on hidden Markov model and block feature matching[J]. Laser & Optoelectronics Progress, 2017, 54(9): 091006.

张宏伟, 张凌婕, 袁小锋, 宋执环. 基于离散余弦变换特征和隐马尔科夫模型的铜熔炼过程烟雾分级[J]. 激光与光电子学进展, 2018, 55(12): 121504. Hongwei Zhang, Lingjie Zhang, Xiaofeng Yuan, Zhihuan Song. Smoke Classification in Copper Smelting Process Based on Discrete Cosine Transform Features and Hidden Markov Model[J]. Laser & Optoelectronics Progress, 2018, 55(12): 121504.

本文已被 1 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!