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  1. Myanmar Institute of Information Technology
  1. Myanmar Institute of Information Technology
  2. Faculty of Computer Science

Semantic Labeling of natural Scene Images Using Color Features

http://hdl.handle.net/20.500.12678/0000007728
http://hdl.handle.net/20.500.12678/0000007728
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0af831e9-f74d-425d-8de2-b8fb36a150d2
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Semantic Semantic Labeling of natural Scene Images Using Color Features.pdf (836 KB)
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Journal article
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Publication
Title
Title Semantic Labeling of natural Scene Images Using Color Features
Language en
Publication date 2018-08-28
Authors
Kyawt Kyawt Htay
G R Sinha
Hanni Htun
New Ni Kyaw
Description
Scene image classification systems firstly need to locate the objects, and then classify the whole image. The color feature is important to describe the properties of an image surface. The paper presents a framework for scene images to label local regions using color features. The paper uses maker-controlled watershed algorithm to segment the input image into regions. This paper uses the segmented regions as a basic input unit, and then extracts Color Histogram (CH) and Color Moment (CM) features in HSV space. This system performs labeling using 3-layer Feed Forward Neural Network (FFNN) classifier. The system tests accuracy on public Microsoft Research Cambridge (MSRC) 9-class dataset.
Keywords
Scene classification, Color features, Color moment, Color histogram, Semantic concepts
Journal articles
Issue 2
CSVTU International Journal of Biotechnology, Bioinformatics and Biomedical
Pages 67–71
Volume 4
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