Browse > Article
http://dx.doi.org/10.7471/ikeee.2018.22.2.350

Enhanced Object Recognition System using Reference Point and Size  

Lee, Taehwan (Dept. of Electronic Engineering, Sangmyung University)
Rhee, Eugene (Dept. of Electronic Engineering, Sangmyung University)
Publication Information
Journal of IKEEE / v.22, no.2, 2018 , pp. 350-355 More about this Journal
Abstract
In this paper, a system that can classify the objects in the image according to their sizes using the reference points is proposed. The object is studied with samples. The proposed system recognizes and classifies objects by the size in images acquired using a mobile phone camera. Conventional object recognition systems classify objects using only object size. As the size of the object varies depending on the distance, such systems have the disadvantage that an error may occurs if the image is not acquired with a certain distance. In order to overcome the limitation of the conventional object recognition system, the object recognition system proposed in this paper can classify the object regardless of the distance with comparing the size of the reference point by placing it at the upper left corner of the image.
Keywords
Object Recognition; Image Processing; Binarization; Benchmark; Classification;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 H. Won and K. Lee. "Fast Hough Circle Detection using Motion in Video Frames," Journal of Korean Society for Internet Information, Vol. 11, No. 6, pp. 31-39, 2010.
2 S. Chae and K. Jun, "Automatic Coin Calculation System using Circular Hough Transform and Post-processing Techniques," Journal of Korea Multimedia Society, Vol. 17, No. 4, pp. 413-419, 2014. DOI: 10.9717/kmms.2014.17.4.413   DOI
3 D. Comaniciu, V. Ramesh, and P. Meer, "Kernel-basaed Object Tracking," IEEE Trans. Patt. Analy. Mach. Intel, Vol. 25, pp. 564-575, 2003. DOI: 10.1109/TPAMI.2003.1195991   DOI
4 S. Chae and K. Jun, "Automatic Coin Calculation System using Circular Hough Transform and Post-processing Techniques," Journal of Korea Multimedia Society, Vol. 17, No, pp. 413-419, 2014. DOI : 10.9717/kmms.2014.17.4.413   DOI
5 J. Lee, J. Lee, and C. Hyun, "Coin Recognition and Classification using Digital Image Processing." Journal of Korean Institute of Intelligent Systems, Vol. 22, No. 1, pp. 7-11, 2012. DOI : 10.5391/JKIIS.2012.22.1.7   DOI
6 J. Choi and C. Kim, "Interval Hough Transform For Prominent Line Detection," Journal of Korea Multimedia Society, Vol. 16, No. 11, pp. 1288-1296, 2013. DOI : 10.9717/kmms.2013.16.11.1288   DOI
7 P. M. Merlin and D. J. Farber, "A Parallel Mechanism for Detecting Curves in Pictures," IEEE Trans. Computer, Vol. 24, pp. 96-98, 1975. DOI: 10.1109/T-C.1975.224087
8 S. Malik, P. Bajaj and M. Kaur, "Sample Coin Recognition System using Artificial Neural Network on Static Image Dataset Network on Static Image Dataset," International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 4, Issue 1, pp. 762-770, 2014
9 T. Kailath, "The Divergence and Bhattacharyya Distance Measures in Signal Selection," IEEE Trans. Communication Technology, Vol. 15, No. 1, pp. 52-60, 1996. DOI: 10.1109/TCOM.1967.1089532
10 J. Shi and C. Tomasi, "Good Features to Track," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 593-600, 1994. DOI: 10.1109/CVPR.1994.323794
11 S. Avidan, "Support Vector Tracking," IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 184-191, 2001. DOI: 10.1109/CVPR.2001.990474
12 J. Lym, Y. Lee, S. Moon, and S. Yang, "Detection of Circle and Rectangle Image by Hough Transform for a Tape Substrate Alignment," Journal of Institute of Control, Robotics and Systems, Vol. 37, pp. 140-144, 2008.
13 J. Canny, "A Computational Approach to Edge Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, pp. 679-698, 1986. DOI: 10.1109/TPAMI.1986.4767851