Title :
Color and wavelet based identification of urban and agricultural area using texture features in satellite images
Author :
Umaselvi, M. ; Kumar, Sahoo Subhendu ; Athithya, M.
Author_Institution :
Dept. of Inf. Technol., Vivekanandha Coll. of Eng. for Women, Tiruchengode, India
Abstract :
This paper represents unsupervised method of color based segmentation using clustering to classify vegetated and urban area in Satellite images. Now a day due to the progresses in spatial resolution of satellite imagery, the methods of segment-based image analysis for generating and updating geographical information are becoming more important. In this work, one method proposed a segmentation of various clusters by La*b* color space and Texture Feature was analyzed. The Second method proposed a segmentation of image by wavelet and Texture Feature was analyzed. Algorithm is verified for simulated images and applied for a selected satellite image processing.
Keywords :
agricultural engineering; artificial satellites; feature extraction; geographic information systems; geophysical image processing; image classification; image colour analysis; image resolution; image segmentation; image texture; pattern clustering; wavelet transforms; agricultural area; color based identification; color based segmentation; geographical information; image segmentation; satellite image processing; satellite imagery; segment-based image analysis methods; simulated images; spatial resolution; texture feature; unsupervised method; urban area classification; vegetated area classification; wavelet based identification; Classification algorithms; Clustering algorithms; Feature extraction; Image color analysis; Image segmentation; Partitioning algorithms; Satellites; Euclidean Metric; K-Means; La∗b∗ colour space;
Conference_Titel :
Green High Performance Computing (ICGHPC), 2013 IEEE International Conference on
Conference_Location :
Nagercoil
Print_ISBN :
978-1-4673-2592-9
DOI :
10.1109/ICGHPC.2013.6533914
