Wood Image Annotation Using Gabor Texture Feature

Nowadays due to quick development in digital images devices and using different imaging tools such as mobile, camera and so on, a huge numbers of images are available. Therefore, efficient management of these images especially by computers is one of challenges in this field. In recent years, automatic image annotation is a problem that is still open widely because of semantic gap between low level features and content of image. Image annotation techniques are automatically assigning a few relevant text keywords to test images, which reflect their visual image contents. This paper doesnʹt a wood classification and the aim of this work has an automatic image annotation for wood texture images. In this paper, Wood Image Annotation for the first time is presented. We used the Gabor filters for wood texture features extraction. After this, we compare the similarity of features vector extracted from the training images and the test images. Experimental results show that the proposed method applying Gabor filter has significant impact on system performance.