A Construction of the Variable Texture Feature Model using SOM of SOMs

Abstract

Nowadays, the efficient searching system and techniques which acquire the new knowledge correctly from the digital image database is needed. Using image texture feature including useful information is effective for understanding and describing the database. In this paper, the Variable Texture Feature Model using SOM of SOMs (SOMn) method which represent the overall database image feature information is proposed. The correct Variable Texture Feature Model is not only useful for the index to texture classification but also can create new images from known images. Experiment shows the Variable Texture Feature Model has the effectivity to supplement the texture feature for classification, and can select the image which represent the texture class automatically, create the new texture images from known images.