期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：5
页码：5996-6001
出版社：IJECS
摘要：The recognition of wood species is needed is many areas like construction industry, furniture manufacturing. Wood istraditionally classified by human experts. But human identification of wood type is not accurate and the manual identification is a timeconsuming process. So in this paper, an intelligent recognition for identification of wood species was developed. This paper uses imageenhancement as a preprocessing techniques and uses a new method which divides the image into several blocks known as image blocking.Each block is extracted using gray image and edge detection techniques. In this paper, GLCM (gray-level co-occurrence matrix) is used astexture classification techniques. The GLCMs are generated to obtain three features: contrast, entropy and correlation. The classificationtechnique used to classify the wood species is a correlation. Our experimental results showed that the proposed method can increase therecognition rate up to 95%, which is faster and better than the existing system which gives 85% recognition rate.
