• Ummi Rabaah Hashim Computational Intelligence and Technologies Lab, Faculty of Information & Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia
  • Siti Zaiton Hashim Soft Computing Research Group, Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia
  • Azah Kamilah Muda Computational Intelligence and Technologies Lab, Faculty of Information & Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia



Automated vision inspection, defect detection, wood inspection, timber defect detection, non-destructive testing


Automated inspection has proven to be of great importance in increasing the quality of timber products, optimising raw material resources, increasing productivity as well as reducing error related to human labour. This paper reviews automated inspection of timber surface defects with a special focus on vision inspection. Previous works on sensors utilised are presented and can be used as a reference for future researchers. General approaches to solving the problem of wood surface defect detection can be categorised into segmentation and non-segmenting approaches. The weaknesses and strengths of each approach are discussed along with feature extraction techniques and classifiers implemented in timber surface defect detection. Furthermore, insights into the practicality of implementing automated vision inspection of timber defects were also discussed. This paper shall benefit researchers and practitioners in understanding different approaches, sensors, feature extraction techniques as well as classifiers that have been implemented in automated inspection of timber surface defects, thus providing some direction for future research.


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How to Cite

Hashim, U. R., Hashim, S. Z., & Muda, A. K. (2015). AUTOMATED VISION INSPECTION OF TIMBER SURFACE DEFECT: A REVIEW. Jurnal Teknologi, 77(20).