Shadow Detection from VHR Images using Clustering and Classification

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Sharda Dhoke, Prof. Jayant Adhikari

Abstract

This project mainly focus to get the high resolution color remote sensing image, and also undertaken to remove the shaded region in the both urban and rural area. Some of the existing projects are involved to detect the shaded region and then eliminate that region, but it has some drawbacks. The detection of the edges will be affected mostly by the application of the external parameters. The edge detection process can be more helpful in the detection of the objects so that the objects can be used for further processing. In this process we have implement the Scale Space algorithm is used to detect the shadow region and extract the feature from the shadow region. Scale Space is simplest in region-base image segmentation methods. The concept of Scale Space algorithm is check the neighboring pixels of the initial seed points. Then determine whether those neighboring pixels are added to the seed points or not. In the Scale Space threshold algorithm Pixels are placed in the region based on their properties or the properties of the nearby pixel values. Then the pixel containing the similar properties is grouped together and then the large numbers of pixels are distributed throughout the image.

Article Details

How to Cite
, S. D. P. J. A. (2018). Shadow Detection from VHR Images using Clustering and Classification. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 4(4), 882–886. Retrieved from https://ijfrcsce.org/index.php/ijfrcsce/article/view/1632
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