SOD: Structured Object Detection
R. Rasal1 , N.M. Shahane2
Section:Research Paper, Product Type: Journal Paper
Volume-2 ,
Issue-7 , Page no. 36-39, Jul-2014
Online published on Jul 30, 2014
Copyright © R. Rasal, N.M. Shahane . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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How to Cite this Paper
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IEEE Style Citation: R. Rasal, N.M. Shahane , “SOD: Structured Object Detection,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.7, pp.36-39, 2014.
MLA Style Citation: R. Rasal, N.M. Shahane "SOD: Structured Object Detection." International Journal of Computer Sciences and Engineering 2.7 (2014): 36-39.
APA Style Citation: R. Rasal, N.M. Shahane , (2014). SOD: Structured Object Detection. International Journal of Computer Sciences and Engineering, 2(7), 36-39.
BibTex Style Citation:
@article{Rasal_2014,
author = {R. Rasal, N.M. Shahane },
title = {SOD: Structured Object Detection},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2014},
volume = {2},
Issue = {7},
month = {7},
year = {2014},
issn = {2347-2693},
pages = {36-39},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=203},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=203
TI - SOD: Structured Object Detection
T2 - International Journal of Computer Sciences and Engineering
AU - R. Rasal, N.M. Shahane
PY - 2014
DA - 2014/07/30
PB - IJCSE, Indore, INDIA
SP - 36-39
IS - 7
VL - 2
SN - 2347-2693
ER -
VIEWS | XML | |
3766 | 3641 downloads | 3656 downloads |
Abstract
Detection of foreground structured objects in the images is an essential task in many image processing applications. This paper presents a region merging approach for automatic detection of the foreground objects in the image. The foreground objects are the structured objects with an independent and detectable boundary. The proposed approach identifies objects in the given image based on general properties of the objects without depending on the prior knowledge about specific objects. The regions of the structured objects in the image are separated from the background based on region contrast information. The perceptual organization laws of human visual system are used in the region merging process to identify the boundaries of various objects. The system is adaptive to the image content. The results of the experiments show that the proposed scheme can efficiently extract object boundary from the background.
Key-Words / Index Term
Contrast, Segmentation, Histogram, Thresholding, Region Merging
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