Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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CSTGV03UY6
Mr. Jenopaul.P
The main research objective of this paper is to detecting object boundaries in outdoor scenes of images solely based on some general properties of the real world objects. Here, segmentation and recognition should not be separated and treated as an interleaving procedure. In this project, an adaptive global clustering technique is developed that can capture the non-accidental structural relationships among the constituent parts of the structured objects which usually consist of multiple constituent parts. The background objects such as sky, tree, ground etc. are also recognized based on the color and texture information. This process groups them together accordingly without depending on a priori knowledge of the specific objects. The proposed method outperformed two state-of-the-art image segmentation approaches on two challenging outdoor databases and on various outdoor natural scene environments, this improves the segmentation quality. By using this clustering technique is to overcome strong reflection and over segmentation. This proposed work shows better performance and improve background identification capability.
Mr. Jenopaul.P. 2013. \u201cTwo State of Art Image Segmentation Approaches for Outdoor Scenes\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 13 (GJCST Volume 13 Issue F2): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 102
Country: India
Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision
Authors: Anju.J.A, Mr. Jenopaul.P (PhD/Dr. count: 0)
View Count (all-time): 231
Total Views (Real + Logic): 9499
Total Downloads (simulated): 2415
Publish Date: 2013 04, Tue
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The main research objective of this paper is to detecting object boundaries in outdoor scenes of images solely based on some general properties of the real world objects. Here, segmentation and recognition should not be separated and treated as an interleaving procedure. In this project, an adaptive global clustering technique is developed that can capture the non-accidental structural relationships among the constituent parts of the structured objects which usually consist of multiple constituent parts. The background objects such as sky, tree, ground etc. are also recognized based on the color and texture information. This process groups them together accordingly without depending on a priori knowledge of the specific objects. The proposed method outperformed two state-of-the-art image segmentation approaches on two challenging outdoor databases and on various outdoor natural scene environments, this improves the segmentation quality. By using this clustering technique is to overcome strong reflection and over segmentation. This proposed work shows better performance and improve background identification capability.
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