Interactive Image Segmentation using Edge Point Techniques (EPT) for Background Subtraction and Object Tracking

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2017 by IJETT Journal
Volume-49 Number-1
Year of Publication : 2017
Authors : R.Neela, S. Lordhu Adaikala Mary
DOI :  10.14445/22315381/IJETT-V49P210

Citation 

R.Neela, S. Lordhu Adaikala Mary "Interactive Image Segmentation using Edge Point Techniques (EPT) for Background Subtraction and Object Tracking", International Journal of Engineering Trends and Technology (IJETT), V49(1),64-68 July 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
This paper focus on developing interactive image segmentation using Edge Point Technique(EPT). There are a lot of Image segmentation techniques are used in image processing such as adaptive constraint propagation, mean shifting techniques, graph based Segmentation, hybrid segmentation etc. The proposed research uses Edge Point Technique (EPT) for Background and Foreground Separation. EPT makes decisions based on particular pixel information and are effective when the moderation levels of the objects fall squarely outside the range of levels in the background. EPT generates pairwise constraints and performs seed propagation. Pairwise constraints in EPT propagate characteristics of the user’s interactive information through the whole image and effectively preserve global discriminative data coherence, thus avoiding bias caused by the limited interactive information. Seed propagation in EPT significantly reduces the computational complexity in interactive image segmentation by decomposing the learning procedure of an image into blocks. The method first extract features from superpixels obtained by existing threshold based segmentation in an image and Pairwise constraints are generated from the user’s interactive information. Next, EPT performs seed propagation on both features and pairwise constraints to learn the global structure in an image. Experimental results demonstrate that the proposed EPT successfully segments foreground objects from the background and remarkably acceptable computational costs.

 References

[1] Leo grady, Random walk for Image Segmentation IEEE transaction ,VOl 28,NO.11 ,Nov 2006.
[2] T. N. A. Nguyen, J. Cai, J. Zhang, and J. Zheng, ?Robust interactive image segmentation using convex active contours, IEEE Trans. ImageProcess., vol. 21, no. 8, pp. 3734–3743, Aug. 2012.
[3] Stanley osher , Ronald P.Fedkiw, ? An Overview :Level set Method, IEEE Trans.Pattern analy., Vol.43, Sep 2005.
[4] B. Peng, L. Zhang, and D. Zhang, ?Automatic image segmentation by dynamic region merging, IEEE Trans. Image Process., vol. 20, no. 12,pp. 3592–3605, Dec. 2011.
[5] Mayank Jain and Divakar Singh, ?An Efficient Technique for Image Retrieval from the Large Database on the Basis of Color and Texture, International Journal of Computer Applications (0975 – 8887) Volume 145 – No.7, July 201
[6] Kranthi kumar, ?content based image retrieval ?, National conference on Advances in information Security(NCAIS)-2010.
[7] B. L. Price, B. Morse, and S. Cohen, ?Geodesic graph cut for interactiveimage segmentation, in Proc. IEEE Conf. Comput. Vis. PatternRecognit., Jun. 2010, pp. 3161–3168.
[8] Y. Zhang, H. Song, J. Gu, S. Yu, and J. Yang, ?Interactive object extraction using template matching and hierarchical graph cuts, in Proc. Int. Conf. Audio Lang.Image Process., Nov. 2010, pp. 851–858.
[9] Vrushali D. Mendhule, Gaurav Soni and Alesh Sharma, ?Interactive Image Segmentation Using Combined MRF and Ant Colony Optimization, International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume 4 Issue 6 June 2015
[10] Jian Guan, Guoping ,An Interactive Image Segmentation using Optimization with Statistical Priors, International conference of statistics - 2015
[11] Ning Du, Xiaofei Wang, Jianhua Guo and Meidong Xu, ?Attraction Propagation: A User-FriendlyInteractive Approach for Polyp Segmentation in Colonoscopy Images, PLOS ONE DOI:10.1371 journal.pone.0155371 May 18, 2016.
[12] Michael Bleyer, Object Stereo Joint Stereo Matching and Object Segmentation, 2015
[13] Alisha Abraham, image segmentation based on harmonic functions & reconstructions, 2013
[14] Mrs. Sprooha Athalye , Mr. Devendra Gadade , Mr. Pankaj Kadam , Mr. Onkar Ambekar " Study on Universal Background Subtraction Algorithm for Videos ", International Journal of Engineering Trends and Technology (IJETT), V20(5),248-251 Feb 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
[15] A New change detection benchmark dataset in IEEE workshop at CVPR 2012, Downloaded from www.changedetection.net
[16] Van Rijsbergen,V.J, information retrieval, Butterworth 2nd edition.
[17] Banejee, A;Chitnis, False Positive:A survey, Whatls.com.Retrieved 26 August 2016.

Keywords
Image segmentation, Background subtraction, Feature extraction and object tracking. Put your keywords here, keywords are separated by comma.