Automated Extraction of Image Features from Geospatial Imagery in form of Grids and Identification of Images using its Corresponding Grid-id

  • Ganesh Chirkhare Student Dept. of Computer Science and Engg., G. H. Raisoni Academy of Engg. and Technology, Nagpur, Maharashtra, India

Abstract

This paper advances a new approach to implement spatial modeler
scripting to subset the image using shapefile and searching technique
for image subset, the employed professionals at MRSAC were facing the
problem while performing the process of image sub setting and searching
different subset images. They have to import the grid repeatedly
while perceiving the image and plotting the region which needs to
be clipped. After sub-setting the image, if any mismatch or improper
clipping is observed then the complete process needs to be restarted
from scratch, which would not be preferable while working with large
datasets consisting many different images. To improve this work, flow
an operative method has been designed known as spatial modeler for
doing the task in an effective and sensitive manner. The clients also have
to search for the set of clipped image, the employees at MRSAC search
the folder manually which takes a considerable amount of time, to
minimize this practice a searching mechanism also needs to be designed
and implemented to search the image subset using its unique grid-id


How to cite this article:
Chirkhare G, Jha R, Gadicha V. Automated
Extraction of Image Features from Geospatial
Imagery in form of Grids and Identification of
Images using its Corresponding Grid-id. J Adv
Res Image Proc Appl 2020; 3(1): 14-18.

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Published
2021-10-04
How to Cite
CHIRKHARE, Ganesh. Automated Extraction of Image Features from Geospatial Imagery in form of Grids and Identification of Images using its Corresponding Grid-id. Journal of Advanced Research in Image Processing and Applications, [S.l.], v. 3, n. 1, p. 14-18, oct. 2021. Available at: <https://thejournalshouse.com/index.php/image-pocessing-applications/article/view/488>. Date accessed: 30 nov. 2021.