1. CONTRIBUTION AND COMBINATION OF DIFFERENT WOOD SECTIONS IN SPECIES RECOGNITION USING IMAGE TEXTURE ANALYSIS METHODS.
- Author
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BARMPOUTIS, Panagiotis
- Subjects
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IMAGE analysis , *MATERIALS texture , *PATTERN perception , *COMPUTER vision , *IMAGE fusion - Abstract
The recognition of wood species is a laborious process, which is performed by experts, who attempt to distinguish the different species in different wood sections based on their macroscopic and microscopic characteristics. Most of these characteristics can be observed in the transverse or cross section of woods. According to experts, the next most important surface for wood species recognition is the tangential section while significant information can also be obtained from the radial section of woods. Based on the recent advances in the area of computer vision and pattern recognition, most researchers have proposed imagebased approaches attempting to address the problem either in microscopic or macroscopic scale. The main limitation is that in many cases there are some features that are not visible in each wood section. Firstly, we examine the contribution of each section in wood species recognition using two different computer-based texture analysis methods. Furthermore, we compare wood species recognition methods for both grayscale images and colorscale images. Finally, we propose a novel fusion method and we demonstrate that wood species recognition accuracy can be increased by fusing features from different wood sections. For the evaluation of the proposed method, a dataset, namely "WOOD-AUTH", consisting of more than 4272 wood images of twelve common wood species, was used. [ABSTRACT FROM AUTHOR]
- Published
- 2017