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HYBRID ANN AND FIREWORKS ALGORITHM FOR REAL-TIME SOFTWARE RELIABILITY PREDICTION

Ivy Botchway Felix Larbi Aryeh Boniface Kayode Alese
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Shadow Detection and Removal based on Automatic Threshold and Boundary Analysis

by Rakesh Kumar Das, Madhu Shandilya
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 17
Year of Publication: 2019
Authors: Rakesh Kumar Das, Madhu Shandilya
10.5120/ijca2019918973

Rakesh Kumar Das, Madhu Shandilya . Shadow Detection and Removal based on Automatic Threshold and Boundary Analysis. International Journal of Computer Applications. 178, 17 ( Jun 2019), 17-21. DOI=10.5120/ijca2019918973

@article{ 10.5120/ijca2019918973,
author = { Rakesh Kumar Das, Madhu Shandilya },
title = { Shadow Detection and Removal based on Automatic Threshold and Boundary Analysis },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2019 },
volume = { 178 },
number = { 17 },
month = { Jun },
year = { 2019 },
issn = { 0975-8887 },
pages = { 17-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number17/30626-2019918973/ },
doi = { 10.5120/ijca2019918973 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:50:40.713584+05:30
%A Rakesh Kumar Das
%A Madhu Shandilya
%T Shadow Detection and Removal based on Automatic Threshold and Boundary Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 17
%P 17-21
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The objects extraction from their background could be a difficult assignment. Since one threshold or structure threshold certainly fails to resolve doubt , in this paper, we have proposed a brand new technique that automatically observe the edge to exactly discriminate pixels as foreground or background using automatic threshold mechanism. By first distinguishing boundary, its associated curvatures, and edge response, used as benchmark to gauge the possible location of the boundary.Results show that the projected technique systematically performs well in various illumination conditions, as well as indoor, outdoor, moderate, sunny, and rainy cases. By an examination with an empirical evidence in every case, the error rate and the shadow detector index indicate a correct detection, that shows substantial improvement as compared with alternative existing ways.

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Index Terms

Computer Science
Information Sciences

Keywords

Boundary evaluation curvature edge error rate foreground extraction gradient map shadow detector index threshold.

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