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Reseach Article

A Novel Approach for the Implementation of Classification Algorithms for Detecting Shadow and Non-Shadow Regions of an Image

by Kamaljit Kaur, Heena Chawla
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 47 - Number 20
Year of Publication: 2012
Authors: Kamaljit Kaur, Heena Chawla
10.5120/7306-0520

Kamaljit Kaur, Heena Chawla . A Novel Approach for the Implementation of Classification Algorithms for Detecting Shadow and Non-Shadow Regions of an Image. International Journal of Computer Applications. 47, 20 ( June 2012), 33-37. DOI=10.5120/7306-0520

@article{ 10.5120/7306-0520,
author = { Kamaljit Kaur, Heena Chawla },
title = { A Novel Approach for the Implementation of Classification Algorithms for Detecting Shadow and Non-Shadow Regions of an Image },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 47 },
number = { 20 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 33-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume47/number20/7306-0520/ },
doi = { 10.5120/7306-0520 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:42:23.313643+05:30
%A Kamaljit Kaur
%A Heena Chawla
%T A Novel Approach for the Implementation of Classification Algorithms for Detecting Shadow and Non-Shadow Regions of an Image
%J International Journal of Computer Applications
%@ 0975-8887
%V 47
%N 20
%P 33-37
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Many image analysis tasks require a classification procedure to identify the shadowed and non-shadowed areas of an image, so that once the shadowed areas are known, the clarity of the image can be improved. The main aim is to detect the anomalous regions of an image. There are numerous techniques of doing so. One of the best ways is to find hyper plane that can be identified to find the difference between the shadow and non shadow areas in the image by using classification algorithm. Thus this research will be to compare various classifiers on the basis of various parameters that which one proves the best in terms of identifying the boundary of shadow and non shadow areas in images. The classification algorithms used in this case would be Support Vector machine (SVM), K- Nearest neighbour (KNN) and Bayesian networks.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Shadow Hyper Plane Support Vector Machine (svm) K-nearest Neighbor(knn) Bayesian Classifier Segmentation Seed Points Scene Analysis True Positive True Negative False Positive Negative Sensitivity Specificity Accuracy