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

Semantic Concepts Classification on Outdoor Scene Images Based on Region-Based Approach

http://hdl.handle.net/20.500.12678/0000007723
http://hdl.handle.net/20.500.12678/0000007723
60179c6a-e10a-418e-9d01-3b62dc2f369e
fe702ef3-3743-4e28-bb88-f6e23174781f
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Semantic Semantic Concepts Classification on Outdoor Scene Images Based on Region-Based Approach.pdf (710 KB)
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Journal article
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Title
Title Semantic Concepts Classification on Outdoor Scene Images Based on Region-Based Approach
Language en
Publication date 2014-12-16
Authors
Kyawt Kyawt Htay
Nyein Aye
Description
Outdoor scene analysis is a complex problem for both image processing and pattern recognition domains. There are two methods of segmenting images to look for objects in an image, block-based and region-based. Region-based method can provide some useful information about objects even though segmentation may not be perfect. There are three phases in this system: segmentation, features extraction and classification. The basic idea of this system is to classify local image regions into semantic concept classes such as tree, sky and road etc. In this paper, modified Marker-Controlled Watershed (MCWS) algorithm is proposed. Firstly, the modified (MCWS) algorithm is used to segment input image. And then, texture feature vectors are extracted from segmented regions by Gray-Level Co-occurrence Matrix (GLCM). Finally, classification is performed by 3-layer Artificial Neural Network (ANN). This system is applied on real scene images dataset.
Keywords
Marker-controlled watershed, outdoor scene analysis, texture
Journal articles
Issue-6
Internal Journal of Future Computer and Communication
Pages 427-431
Volume 3
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