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Efficient Object Localization using Color Correlation Back-projection
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  • Journal title : Journal of Digital Convergence
  • Volume 14, Issue 5,  2016, pp.263-271
  • Publisher : The Society of Digital Policy and Management
  • DOI : 10.14400/JDC.2016.14.5.263
 Title & Authors
Efficient Object Localization using Color Correlation Back-projection
Lee, Yong-Hwan; Cho, Han-Jin; Lee, June-Hwan;
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Localizing an object in image is a common task in the field of computer vision. As the existing methods provide a detection for the single object in an image, they have an utilization limit for the use of the application, due to similar objects are in the actual picture. This paper proposes an efficient method of object localization for image recognition. The new proposed method uses color correlation back-projection in the YCbCr chromaticity color space to deal with the object localization problem. Using the proposed algorithm enables users to detect and locate primary location of object within the image, as well as candidate regions can be detected accurately without any information about object counts. To evaluate performance of the proposed algorithm, we estimate success rate of locating object with common used image database. Experimental results reveal that improvement of 21% success ratio was observed. This study builds on spatially localized color features and correlation-based localization, and the main contribution of this paper is that a different way of using correlogram is applied in object localization.
Object Localization;Object Detection;Spatial Color Correlation;Correlogram Backprojection;
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디지털융복합연구, 2016. vol.14. 11, pp.143-148 crossref(new window)
Kyoungro Yoon, Youngseop Kim, Je-Ho Park, Jaime Delgado, Akio Yamada, Frederic Dufaux, Ruben Tous, "JPSearch: New International Standard Providing Interoperable Framework for Image Search and Sharing", Signal Processing: Image Communication, vol.27, issue.7, pp.709-721, 2012. crossref(new window)

P. Radhakrishnan, A. Clementking, "Determination of Object Similarity Closure using Shared Neighborhood Connectivity", Journal of the Korea Convergence Society, vol.5, no.3, pp.41-44, 2014. crossref(new window)

Roger M. Dufour, Eric L. Mill, Nikolas P. Galatsanos, "Template Matching based Object Recognition with Unknown Geometric Parameters", IEEE Transactions on Image Processing, vol.11, no.12, pp.1385-1396, 2002. crossref(new window)

Sanghyuk Lee, "Grouping DNA Sequence with Similarity Mearure and Application", Journal of the Korea Convergence, vol.4, no.3, pp.35-41, 2013.

Vivek Jain, Neha Sahu, "A Survey on Content based Image Retrieval", International Journal of Engineering Research and Applications, vol.3, issue.4, pp.1166-1169, 2013.

Keyuri M. Zinzuvadia, Bhavesh A. Tanawala, Keyur N. Brahmbhatt, "A Survey on Feature based Image Retrieval using Classification and Relevance Feedback Techniques", International Journal of Innovative Research in Computer and Communication Engineering, vol.3, issue.1, pp.508- 513, 2015.

Olga Russakovsky, Yuanqing Lin, Kai Yu, Li Fei-Fei, "Object-centric Spatial Pooling for Image Classification", Lecture Notes in Computer Science, vol.7573, pp.1-15, 2012.

Kevin Murphy, Antonio Torralba, Daniel Eaton, William Freeman, "Object Detection and Location using Local and Global Features", Lecture Notes in Computer Science, vol.4170, pp.382-400, 2006.

John R. Smith, "Integrated Spatial and Feature Image Systems: Retrieval, Analysis and Compression", Ph.D. Thesis, Columbia University, USA, 1997.

Hong-Hee Kim, Jae-Heung Lee, "Development of a License Plate Recognition System using Template Matching Method in Embedded System", Journal of Institute of Korean Electrical and Electronics Engineers, vol.15, no.4, pp.274-280, 2011.

Tali Delel, Shaul Oron, Michael Rubinstein, Shai Avidan, William T. Freeman, "Best-Buddies Similarity for Robust Template Matching", International Conference on Computer Vision and Pattern Recognition, pp.2021-2029, 2015.

Hee-June Han, Jong-Yun Lee, "Algorithm of Converged Corner Detection-based Segmentation in the Data Matrix Barcode", Journal of the Korea Convergence, vol.6, no.1, pp.7-16, 2015. crossref(new window)

Alper Yilmaz, Omar Javed, Mubarak Shah, "Object Tracking: A Survey", ACM Computing Surveys, vol.38, issue.4, no.13, pp.1-45, 2006. crossref(new window)

Sanghyuk Lee, Yujia Zhai, "Relation between Certainty and Uncertainty with Fuzzy Entropy and Similarity Measure", Journal of the Korea Convergence Society, vol.5, no.4, pp.155-161, 2014. crossref(new window)

Christoph H. Lampert, Matthew B. Blaschko, Thomas Hofmann, "Beyond Sliding Windows: Object Localization by Efficient Subwindow Search", IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.

Jamal Malki, Nozha Boujemaa, Chahab Naster, Alexandre Winter, "Region Queries without Segmentation for Image Retrieval by Content", Lecture Notes in Computer Science, vol.1614, pp.115-122, 2002.

Michael Wirth, Ryan Zaremba, "Flame Region Detection based on Histogram Backprojection", Canadian Conference Computer and Robot Vision, pp.167-174, 2010.

Jing Huang, S. Ravi Kumar, Mandar Mitra, Wei Jing Zhu, Ramin Zabih, "Spatial Color Indexing and Applications" International Journal of Computer Vision, vol.35, no.3, pp.245-268, 1999. crossref(new window)

Jong-Hun Park, Gang-Seong Lee, Sang-Hun Lee, "A Study on the Convergence Technique enhaced GrabCut Algorithm using Color Histogram and Modified Sharpening Filter", Journal of the Korea Convergence Society, vol.6, no.5, pp.1-8, 2015.

Mika Rautiainen, Timo Ojala, "Color Correlograms in Image and Video Retrieval", Finnish Conference on Artificial Intelligence, pp.1-10, 2002.

Jing Huang, S. Ravi Kumar, Mandar Mitra, Wei0Jing Zhu, Ramin Zabih, "Image Indexing using Color Correlograms", IEEE Conference on Computer Vision and Pattern Recognition, pp.762-768, 1997.