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General Information
Editor-in-chief

Prof. Pascal Lorenz
University of Haute Alsace, France
 
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2014Vol.3(6): 427-431 ISSN: 2010-3751
DOI: 10.7763/IJFCC.2014.V3.341

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

Kyawt Kyawt Htay and Nyein Aye
Abstract—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.

Index Terms—Marker-controlled watershed, outdoor scene analysis, texture.

Kyawt Kyawt Htay1is with University of Computer Studies, Mandalay, Myanmar (e-mail: kyawtkyawthtay@gmail.com).
Nyein Aye2 is with the head of the Department of Hardware, University of Computer Studies Mandalay, Myanmar (e-mail:nyeinaye@gmail.com).

[PDF]

Cite: Kyawt Kyawt Htay and Nyein Aye, "Semantic Concepts Classification on Outdoor Scene Images Based on Region-Based Approach," International Journal of Future Computer and Communication vol. 3, no. 6, pp. 427-431, 2014.

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