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International Journal of Systems Science Volume 40, 2009 - Issue 2: Innovative Production Machines and Systems, Guest Editors: Duc-Truong Pham, Anthony Soroka and Eldaw Eldukhri
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Original Articles

Automated visual inspection system for wood defect classification using computational intelligence techniques

Gonzalo A. Ruz Manufacturing Engineering Centre, Cardiff University, Cardiff, UKCorrespondence[email protected]
,
Pablo A. Estévez Department of Electrical Engineering, Universidad de Chile, Casilla 412-3, Santiago, Chile
&
Pablo A. Ramírez Department of Electrical Engineering, Universidad de Chile, Casilla 412-3, Santiago, Chile
Pages 163-172 | Received 02 May 2006, Published online: 14 Feb 2009

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Hui Li, Lu-Yao Hong, Qing Zhou & Hai-Jie Yu. (2015) The assisted prediction modelling frame with hybridisation and ensemble for business risk forecasting and an implementation. International Journal of Systems Science 46:11, pages 2072-2086.
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M. Alper Selver, Vural Avşar & Hakan Özdemir. (2014) Textural fabric defect detection using statistical texture transformations and gradient search. The Journal of The Textile Institute 105:9, pages 998-1007.
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Hui Li, Diego Andina & Jie Sun. (2013) Multiple proportion case-basing driven CBRE and its application in the evaluation of possible failure of firms. International Journal of Systems Science 44:8, pages 1409-1425.
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Hailong Ma & Mingwei Shao. (2023) Algorithm for automatic optimizing cross-cut saw based on computer vision techniques. Engineering Research Express 5:4, pages 045022.
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Yuming Cui, Shuochen Lu & Songyong Liu. (2023) Real-time detection of wood defects based on SPP-improved YOLO algorithm. Multimedia Tools and Applications 82:14, pages 21031-21044.
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Ömer Nedim Kenger & Eren Özceylan. (2023) Fuzzy min–max neural networks: a bibliometric and social network analysis. Neural Computing and Applications 35:7, pages 5081-5111.
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Andrzej Sioma & Bartosz Lenty. (2022) Detection of Fungal Infections on the Wood Surface Using LTM Imaging. Applied Sciences 13:1, pages 490.
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Dongjie Li, Zilei Zhang, Baogang Wang, Chunmei Yang & Liwei Deng. (2022) Detection method of timber defects based on target detection algorithm. Measurement 203, pages 111937.
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Xiao Wang. (2022) An optimized wood knots recognition scheme based on double detection. An optimized wood knots recognition scheme based on double detection.
Sung-Wook Hwang, Taekyeong Lee, Hyunbin Kim, Hyunwoo Chung, Jong Gyu Choi & Hwanmyeong Yeo. (2022) Classification of wood knots using artificial neural networks with texture and local feature-based image descriptors. Holzforschung 76:1, pages 1-13.
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Yong Wang, Wei Zhang, Rui Gao, Zheng Jin & Xiaohuan Wang. (2021) Recent advances in the application of deep learning methods to forestry. Wood Science and Technology 55:5, pages 1171-1202.
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Xiaoxia Yang, Xin Gao, Tao Wang, Kepeng Yang, Chengxin Hu, Xiaoping Liu & Yucheng Zhou. (2021) Design and Implementation of the Wood Knot Recognition System Based on Matlab GUI. Design and Implementation of the Wood Knot Recognition System Based on Matlab GUI.
Andre Marasca, Andre Backes, Fabio Favarim, Marcelo Teixeira & Dalcimar Casanova. (2021) EDT Method for Multiple Labelled Objects Subject to Tied Distances. International Journal of Automation and Computing 18:3, pages 468-479.
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Martin Kryl, Lukas Danys, Rene Jaros, Radek Martinek, Pavel Kodytek & Petr Bilik. (2020) Wood Recognition and Quality Imaging Inspection Systems. Journal of Sensors 2020, pages 1-19.
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Ting He, Ying Liu, Yabin Yu, Qian Zhao & Zhongkang Hu. (2020) Application of deep convolutional neural network on feature extraction and detection of wood defects. Measurement 152, pages 107357.
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Marcin Bator & Katarzyna Śmietańska. (2019) Constraint-based algorithm to estimate the line of a milling edge. Machine Graphics and Vision 28:1/4, pages 59-67.
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Ivan Aleksi, Filip Susac & Tomislav Matic. (2019) Features Extraction and Texture Defect Detection of Sawn Wooden Board Images. Features Extraction and Texture Defect Detection of Sawn Wooden Board Images.
Fang Xie, Renwen Chen, Qinbang Zhou, Yilin Zhao & Tao Sui. (2019) An Adaptive Defect Detection Technology for Car-Bodies Surfaces. An Adaptive Defect Detection Technology for Car-Bodies Surfaces.
Ahmad Ostovar, Bruce Talbot, Stefano Puliti, Rasmus Astrup & Ola Ringdahl. (2019) Detection and classification of Root and Butt-Rot (RBR) in Stumps of Norway Spruce Using RGB Images and Machine Learning. Sensors 19:7, pages 1579.
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Xiaoquan Yue, Lihai Wang, James P. Wacker & Zhiming Zhu. (2019) Electric resistance tomography and stress wave tomography for decay detection in trees—a comparison study. PeerJ 7, pages e6444.
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Junfeng Hu, Wenlong Song, Wei Zhang, Yafeng Zhao & Alper Yilmaz. (2019) Deep learning for use in lumber classification tasks. Wood Science and Technology 53:2, pages 505-517.
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Ting He, Ying Liu, Chengyi Xu, Xiaolin Zhou, Zhongkang Hu & Jianan Fan. (2019) A Fully Convolutional Neural Network for Wood Defect Location and Identification. IEEE Access 7, pages 123453-123462.
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Xinman Zhang, Weiyong Gong, Haocheng Feng & Xuebin Xu. (2018) Magnetic Ring Detection System Based on Multi-camera Vision Technology. Magnetic Ring Detection System Based on Multi-camera Vision Technology.
C. Iglesias, J. Martínez & J. Taboada. (2018) Automated vision system for quality inspection of slate slabs. Computers in Industry 99, pages 119-129.
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Mathew Flemmer & Liqiong Tang. (2017) Computer vision for automatic accurate plasma arc cutting measurement. Computer vision for automatic accurate plasma arc cutting measurement.
K. Kamal, R. Qayyum, S. Mathavan & T. Zafar. (2017) Wood defects classification using laws texture energy measures and supervised learning approach. Advanced Engineering Informatics 34, pages 125-135.
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Gonzalo A. Ruz. (2016) Improving the performance of inductive learning classifiers through the presentation order of the training patterns. Expert Systems with Applications 58, pages 1-9.
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Ummi Raba’ah Hashim, Siti Zaiton Mohd Hashim & Azah Kamilah Muda. (2016) Performance evaluation of multivariate texture descriptor for classification of timber defect. Optik 127:15, pages 6071-6080.
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Yizhuo Zhang, Sijia Liu, Jun Cao, Chao Li & Huiling Yu. (2015) Wood board image processing based on dual-tree complex wavelet feature selection and compressed sensing. Wood Science and Technology 50:2, pages 297-311.
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Yizhuo Zhang, Sijia Liu, Wenjun Tu, Huiling Yu & Chao Li. (2015) Using computer vision and compressed sensing for wood plate surface detection. Optical Engineering 54:10, pages 103102.
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Yizhuo Zhang, Chao Xu, Chao Li, Huiling Yu & Jun Cao. (2015) Wood defect detection method with PCA feature fusion and compressed sensing. Journal of Forestry Research 26:3, pages 745-751.
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Lanying Lin, Sheng He, Feng Fu & Xiping Wang. (2015) Detection of wood failure by image processing method: influence of algorithm, adhesive and wood species. European Journal of Wood and Wood Products 73:4, pages 485-491.
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Yi-Gang Cen, Rui-Zhen Zhao, Li-Hui Cen, Li-Hong Cui, Zhen-Jiang Miao & Zhe Wei. (2015) Defect inspection for TFT-LCD images based on the low-rank matrix reconstruction. Neurocomputing 149, pages 1206-1215.
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Yizhuo Zhang, Sijia Liu, Jun Cao, Chao Li & Huiling Yu. (2014) A rapid, automated flaw segmentation method using morphological reconstruction to grade wood flooring. Journal of Forestry Research 25:4, pages 959-964.
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Zainul Abdin Jaffery & Ashwani Kumar Dubey. (2013) Architecture of Noninvasive Real Time Visual Monitoring System for Dial Type Measuring Instrument. IEEE Sensors Journal 13:4, pages 1236-1244.
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Verónica Carrera, Patricia Melin & Diana Bravo. 2013. Recent Advances on Hybrid Intelligent Systems. Recent Advances on Hybrid Intelligent Systems 201 210 .
Gonzalo A. Ruz & Duc Truong Pham. (2011) NBSOM: The naive Bayes self-organizing map. Neural Computing and Applications 21:6, pages 1319-1330.
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Du-Ming Tsai, Ming-Chun Chen, Wei-Chen Li & Wei-Yao Chiu. (2012) A fast regularity measure for surface defect detection. Machine Vision and Applications 23:5, pages 869-886.
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Chollada Laofor & Vachara Peansupap. (2012) Defect detection and quantification system to support subjective visual quality inspection via a digital image processing: A tiling work case study. Automation in Construction 24, pages 160-174.
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Vincenzo Piuri & Fabio Scotti. (2010) Design of an Automatic Wood Types Classification System by Using Fluorescence Spectra. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 40:3, pages 358-366.
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Duc Truong Pham & Gonzalo A. Ruz. (2009) Unsupervised training of Bayesian networks for data clustering. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 465:2109, pages 2927-2948.
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