Figure 1.
The three types of images used in computer-aided wood recognition.
Figure 2.
Process of acquiring, selecting and normalizing a single wood sample in the ZAFU-WS 24 wood dataset.
Figure 3.
Texture images from ZAFU WS 24 dataset used in the experiments.
From left to right and top to bottom: Salix wilsonii Seem, Juglans cathayensis ver. Formasana, Juglans regia Linn, Castanea henryi (Skam) Rehd. et Wils, Castanea seguinii Dode, Castanopsis fordii Hance, Castanopsis tibetana Hance, Castanopsis sclerophylla (Lindl.)Schott, Fagus lucida Rehd. et Wils, Quercus acutissima Carruth, Quercus variabilis Blume, Aphananthe aspera Planch, Celtis biondii Pamp, Celtis bungeana Bl., Ulmus changii Cheng, Ulmus parvifolia Jacq, Litsea cubeba (Lour.) Pers, Sassafras tsumu, Photinia prunifolia (Hook. et Arn.) Lindl, Padus racemosa, Evodia fargesii Dode, z.ailanthoides Sieb. et Zucc, Toxicodendron succedaneum (Linn.) O.Kuntze, Meliosma flexuosa Pamp.
Figure 4.
Eight images of a single wood species (Quercus acutissima Carruth).
Figure 5.
(order 0–8; displacement 3×3 pixels) [34]
Figure 6.
Larger masks obtained through dilation.
Figure 7.
Large mask pattern realized by varying spatial interval.
Figure 8.
: (a) Original image; (b) and (c) are MMI outputs of (a) using the 2nd and 7th masks in Fig. 5, respectively.
Figure 9.
Example of length histogram of Fig. 8(b).
Table 1.
Average classification results of HLAC and MMI using two mask groups and two classifiers.
Table 2.
Performance of MMI using different features.
Table 3.
Figure 10.
The experimental results of 30 test experiments.
Figure 11.
Comparison of different classes of original and MMI images.
Figure 12.
Comparison of identical image classes on mask matching images.
Figure 13.
Different configurations of MMIs containing 16 pixel points.
Figure 14.
Example of length histogram (average of all samples).