Image Segmentation Using Improved Genetic Algorithm

Authors(1) :-K. Leelavathi

With the expanding openness to new advancements, the principle issues in locale acknowledgment of remote detecting pictures are: (1) arrangement techniques are reliant on the division quality; and (2) the choice of delegate tests for preparing. The significant test is that the examples shown by the client are not in every case enough to characterize the best division scale. Besides, the sign of tests can be expensive, since it regularly requires to visit considered places in loco. The choice of delegate tests, then again, was bolstered in this work by the improvement of another intelligent characterization approach based on dynamic learning. Critical commitments were likewise acquired concerning the depiction of areas in remote detecting pictures by methods for: an assessment investigation of 19 descriptors; and two new methodologies for accelerating highlight extraction from a progressive system of sectioned districts.

Authors and Affiliations

K. Leelavathi
Assistant Professor, Department of Computer Science and Engineering, Nellore, Andhra Pradesh, India

Arrangement Techniques, Soil, Vegetation, Roof, Road, Buildings, Earth Surface Objects, Hyperspectral Remote Sensing, Remote Sensing Image

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Publication Details

Published in : Volume 3 | Issue 7 | September-October 2018
Date of Publication : 2018-10-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 331-336
Manuscript Number : CSEIT183773
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

K. Leelavathi, "Image Segmentation Using Improved Genetic Algorithm", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 7, pp.331-336, September-October-2018.
Journal URL : http://ijsrcseit.com/CSEIT183773

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