Semantic Labeling of natural Scene Images Using Color Features

Authors

  • Kyawt Kyawt Htay Myanmar Institute of Information Technology, Myanmar
  • G R Sinha, DR Myanmar Institute of Information Technology, Myanmar
  • Hanni Htun Myanmar Institute of Information Technology, Myanmar
  • Nwe Ni Kyaw Myanmar Institute of Information Technology, Myanmar

DOI:

https://doi.org/10.30732/IJBBB.20190402006

Keywords:

Scene classification, Color features, Color moment, Color histogram, Semantic concepts

Abstract

Scene image classification systems firstly need to locate the objects, and then classify the whole image. The color feature is importance 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 extract 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.

References

[1] Fulkerson, B., Vedaldi, A., & Soatto, S. (2009, September). Class segmentation and object localization with superpixel neighborhoods. In 2009 IEEE 12th international conference on computer vision (pp. 670-677). IEEE.
[2] Vogel, J., & Schiele, B. (2004, July). Natural scene retrieval based on a semantic modeling step. In International Conference on Image and Video Retrieval (pp. 207-215). Springer, Berlin, Heidelberg.
[3] Triggs, B., & Verbeek, J. J. (2008). Scene segmentation with CRFs learned from partially labeled images. In Advances in neural information processing systems (pp. 1553-1560).
[4] Htay, K. K., & Aye, N. (2014). Semantic concepts classification on outdoor scene images based on region-based approach. International Journal of Future Computer and Communication, 3(6), 427.
[5] Htay, K. K., & Aye, N. (2016). Regions Labeling in Outdoor Scene Images. In Genetic and Evolutionary Computing (pp. 259-268). Springer, Cham.
[6] Htay, K. K., & Aye, N. (2018, October). Region Labeling in Natural Scene Images. In 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE) (pp. 781-782). IEEE.
[7] Campbell, N. W., Mackeown, W. P., Thomas, B. T., & Troscianko, T. (1996, June). The automatic classification of outdoor images. In International Conference on Engineering Applications of Neural Networks (pp. 339-342).
[8] [9] Raja, S. K., KHADIR, A., SHAIK, A., & AHAMED, S. R. (2009). “Moving Toward Region Based Image Segmentation Techniques: A Study”, Journal of Theoretical and Applied Information Technology (JATIT).
[9] Deswal, M., & Sharma, N. (2014). “A Fast HSV Image Color and Texture Detection and Image Conversion Algorithm”, International Journal of Science and Research (IJSR), 3(6).
[10] Yu, H., Li, M., Zhang, H. J., & Feng, J. (2002, September). "Color Texture Moments for Content Based Image Retrieval", Proceeding IEEE Internal Conference on Image Processing, (Vol. 3, pp. 929-932). IEEE.
[11] Singh, S. M., & Hemachandran, K. (2012). Image retrieval based on the combination of color histogram and color moment. International Journal of Computer Applications, 58(3).
[12] Sonka, M., Hlavac, V., & Boyle, R. (1999). Image processing, analysis, and machine vision second edition. International Thomson, 2.
[13] Criminisi, A. 2004 “Microsoft Research Cambridge Object Recognition Image Database”, Version-1.0.

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Published

2019-09-03

How to Cite

Htay, K. K., Sinha, G. R., Htun, H., & Kyaw, N. N. (2019). Semantic Labeling of natural Scene Images Using Color Features. CSVTU International Journal of Biotechnology, Bioinformatics and Biomedical, 4(2), 67–71. https://doi.org/10.30732/IJBBB.20190402006

Issue

Vol. 4 No. 2 (2019): CSVTU IJBBB

Section

Articles

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