A 2D Texture Image Retrieval Technique based on Texture Energy Filters

In this paper, a database of texture images is analyzed by the Laws’ texture energy measure technique. The Laws’ technique has been used in a number of fields, such as computer vision and pattern recognition. Although most applications use Laws’ convolution filters with sizes of 3× 3 and 5× 5 for extracting image features, our experimental system uses extended resolutions of filters with sizes of 7× 7 and 9× 9. The use of multiple resolutions of filters makes it possible to extract various image features from 2D texture images of a database. In our study, the extracted image features were selected based on statistical analysis, and the analysis results were used for determining which resolutions of features were dominant to classify texture images. A texture energy computation technique was implemented for an experimental texture image retrieval system. Our preliminary experiments showed that the system can classify certain texture images based on texture features, and also it can retrieve texture images reflecting texture pattern similarities.