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| | <p><a href="papers/dp2009-02.pdf">Download</a> (PDF, 168 KB)</p> |
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| | <h3><a name="#dp2009-03">2009/03: Automatic sapstain detection in processed timber through image feature analysis</a></h3> |
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| | <h4>J.D. Deng</h4> |
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| | <p>Sapstain is considered a defect that must be removed from processed wood. So far, research in automatic wood inspection systems has been mostly limited to dealing with knots. In this paper, we extract a number of colour and texture features from wood pictures. These features are then assessed using machine learning techniques via feature selection, visualization, and Þnally classiÞcation. Apart from average colour and colour opponents, texture features are also found to be useful in classifying sapstain. This implies a signiÞcant modiÞcation to the domain understanding that sapstain is mainly a discolourization effect. Preliminary results are presented, with satisfactory classiÞcation performance using only a few selected features. It is promising that a real world wood inspection system with the functionality of sapstain detection can be developed.</p> |
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| | <p><a href="papers/dp2009-03.pdf">Download</a> (PDF, 884 KB)</p> |
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