Author(s)

Alexander Goltsev¹, Vladimir Gritsenko¹, Dušan Húsek²

¹International Research and Training Center of Informational Technologies and Systems, National Academy of Sciences of Ukraine, Kiev, Ukraine.
²Institute of Computer Science, Academy of Sciences of the Czech Republic, Prague, Czech Republic.

The purpose of the research is to develop a universal algorithm for partial texture segmentation of any visual images. The main peculiarity of the proposed segmentation procedure is the extraction of only homogeneous fine-grained texture segments present in the images. At first, an initial seed point is found for the largest and most homogeneous segment of the image. This initial seed point of the segment is expanded using a region growing method. Other texture segments of the image are extracted analogously in turn. At the second stage, the procedure of merging the extracted segments belonging to the same texture class is performed. Then, the detected texture segments are input to a neural network with competitive layers which accomplishes more accurate delineation of the shapes of the extracted texture segments. The proposed segmentation procedure is fully unsupervised, i.e., it does not use any a priori knowledge on either the type of textures or the number of texture segments in the image. The research results in development of the segmentation algorithm realized as a computer program tested in a series of experiments that demonstrate its efficiency on grayscale natural scenes.

Texture Feature, Texture Window, Homogeneous Fine-Grained Texture Segment, Extraction of Texture Segment, Texture Segmentation

Goltsev, A. , Gritsenko, V. and Húsek, D. (2020) Segmentation of Visual Images by Sequential Extracting Homogeneous Texture Areas. Journal of Signal and Information Processing, 11, 75-102. doi: 10.4236/jsip.2020.114005.