5555762
doi
10.35940/ijeat.D7053.049420
oai:zenodo.org:5555762
Blue Eyes Intelligence Engineering & Sciences Publication(BEIESP)
Publisher
E. Menaka
Associate Professor, Vivekanandha College of Engineering for Women, Elayampalayam, Namakkal, Tamilnadu 642247, India.
Region Based Segmentation using TCRM
M. Umaselvi
Associate Professor, P. A. College of Engineering and Technology, Palladam Road, Pollachi, Coimbatore - 642002, India.
issn:2249-8958
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Remote sensing images, Assessment of water region, Feature extraction.
<p>Water Resource is one of the essential supplies of the globe environment which needs to be regularly observed. There is rising need and necessitate in research of water region detection due to the unpredicted natural calamity that guide to financial, environment and individual sufferers. Assessment of water region (WR) and study on its characteristic is very fundamental step for many scheduling, particularly for country like India which made frequent changes on WR. Basically, recognize the WR from Remote sensing images is one of the impressive steps of water possessions organization for a country where it has been used superior than decades for WR detection. Techniques of WR extraction can be examine into three groups: Texture Conditional Rotation Mean (TCRM), feature extraction using TCRM algorithms, Region based segmentation. These methods, though, are of mathematical and statistical approach and little of them look at important uniqueness of multispectral image which is found on land object radiance absorption performance in every sensing spectral bands. In visible and infrared bands, the WR spectral absorption characteristics differ very much from the other earth substance. There are different data bases for the study area which consists of different form and exposure. Results show that TCRM presents adequate well detection for WR as speedy and receiving high accuracy with the suitable threshold rate.</p>
Zenodo
2020-04-30
info:eu-repo/semantics/article
5555761
1633700913.776819
2064475
md5:a40f2d23f2e778ff6f7fc10dbb5db93a
https://zenodo.org/records/5555762/files/D7053049420.pdf
public
2249-8958
Is cited by
issn
International Journal of Engineering and Advanced Technology (IJEAT)
9
4
722-731
2020-04-30