Method of Image Texture Segmentation Using Laws' Energy Measures

This article suggests the method of image segmentation, using Laws` texture energy measures. This method allows identifying segments of images efficiently for their further use in the image processing. Laws` measures describe the image most accurately, resulting in making it easier and more efficient in comparison with the other approaches to allocate separate classes of textures. In order to obtain these measures the sixteen masks are calculated. Resulting energy measures can be provided after applying each of the masks to the image. The developed algorithm was tested using a set of test images. Analysis of the obtained results has showed that in case of visually similar texture images the transition to energy maps significantly improves the correlation coefficient and therefore emphasizes textural features of the images and makes it possible to identify the similarities of textures. In order to evaluate the results of efficiency of developed algorithm properly, its results have been compared to the segmentation method based on matrix matches. It was proved that segmentation based on Laws` measures can detect various types of texture more precisely and with greater speed of operation.