Title :
Image texture analysis using geostatistical information entropy
Author_Institution :
Res. Center for Adv. Inf. Sci. & Technol., Univ. of Aizu, Fukushima, Japan
Abstract :
Extraction of effective features of objects is an important area of research in the intelligent processing of image data. A well-known feature in images is texture which can be used for image description, segmentation and classification. This paper presents a novel texture extraction method using the principles of geostatistics and the concept of entropy in information theory. Experimental results on medical image data have shown the superior performance of the proposed approach over some popular texture extraction methods.
Keywords :
feature extraction; image texture; feature extraction; geostatistical information entropy; image classification; image description; image processing; image segmentation; image texture analysis; information theory; texture extraction; Biomedical imaging; Computed tomography; Educational institutions; Entropy; Feature extraction; Image segmentation; Information entropy; Image classification; entropy; geostatistics; indicator kriging; texture feature;
Conference_Titel :
Intelligent Systems (IS), 2012 6th IEEE International Conference
Conference_Location :
Sofia
Print_ISBN :
978-1-4673-2276-8
DOI :
10.1109/IS.2012.6335160