The week's pick
Random Articles
Reseach Article
Counting Objects using Homogeneous Connected Components
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 63 - Number 21 |
| Year of Publication: 2013 |
| Authors: Jaydeo K. Dharpure, Madhukar B. Potdar, Manoj Pandya |
10.5120/10590-5585
|
Jaydeo K. Dharpure, Madhukar B. Potdar, Manoj Pandya . Counting Objects using Homogeneous Connected Components. International Journal of Computer Applications. 63, 21 ( February 2013), 31-37. DOI=10.5120/10590-5585
Abstract
A very important feature extraction method that is commonly used in computer visions and image processing applications is counting of objects. This paper represents a modified sequential region labeling algorithm which counts the homogeneous region of different objects on image. It is based on 4-connected, 6-connected and 8-connected component technique. These algorithms scan the image pixel by pixel from left to right and top to bottom sequentially and assign a label to every foreground pixels in binary image. Salt and pepper noise is usually prevalent in such images. Removing this noise is an important issue. We propose median filter algorithm to removed such type of noise and obtain better results. This technique may be applied to uniform, non-uniform, regular, irregular objects with different shape, size and file formats. Binary images are obtained from color or greyscale images by proper thresholding. In this proposed method, the regions of various objects are found by region labelling process. These distinct regions are given the number of objects that are present inside the image. This algorithm is implemented on the . net technology. These methods produced good performance in term of accuracy. This is a process oriented task. So the machine having higher processing speed can serve the purpose better.
References
- Akmal Rakhmadi, Nur Zuraifah Syazrah Othman, Abdullah Bade, Mohd Shafry Mohd Rahim and Ismail Mat Amin (2010), "Connected Component Labeling Using Components Neighbors-Scan Labeling Approach" Journal of Computer Science, ISSN 1549-3636, 6 (10): pp 1099-1107.
- Mark A. Foltz (1997), Connected Components in Binary Image 6. 866: Machine Vision December 15.
- Lifeng He, Yuyan Chao, Kenji Suzuki (2012), "A New Two-Scan Algorithm for Labeling Connected Components in Binary Images" WCE July 4 - 6, 2012 vol II, London, U. K. , ISBN: 978-988-19252-1-3.
- Roshan Dharshana Yapa and Koichi Harada (2008), "Connected Component Labeling Algorithms for Gray-Scale Images and Evaluation of Performance using Digital Mammograms" International Journal of Computer Science and Network Security, VOL. 8 No. 6, pp 33-41.
- Tinku acharya and Ajoy K. Ray (2005) "Image Processing Principles and Applications", A John Wiley and Sons Inc. , Publication, ISBN-10: 0471719986, pp 152, 311-312.
- Gonzalez R. C. , and Woods R. E. (2002) "Digital Image Processing" (Second Ed), Prentice Hall, ISBN-10: 0201180758.
- Kenji Suzuki, Isao Horiba, and Noboru Sugie (2003), "Linear-time connected-component labeling based on sequential local operations" Computer Vision and Image Understanding, pp 1-23.
- K. B. Wang, T. L. Chia, Z. Chen (2003), "Parallel execution of a connected component labeling operation on a linear array architecture", J. Inf. Sci. Eng. 19, pp. 353–370.
- P. How-Lung Eng and Kai-Kuang Ma (2001), "Noise Adaptive Soft-Switching Median Filter" IEEE Transactions On Image Processing, Vol. 10, No. 2.
- V. R. Vijaykumar, P. T. Vanathi, P. Kanagasabapathy and D. Ebenezer (2009) "Robust Statistics Based Algorithm to Remove Salt and Pepper Noise in Images" World Academy of Science, Engineering and Technology 35.
- B Ravi Kiran, K R Ramakrishnan and Y Senthil Kumar, Anoop K P, "An Improved Connected Component Labeling by Recursive Label Propagation" Using Divide and Conquer Approach.
- JM Park, CG Looney, HC Chen (2000), "Fast Connected Component Labeling Algorithm Using A Divide and Conquer Technique", Conference on computers and their Applications.
- Kesheng W. , Ekow O. , and Arie S. (2005), "Optimizing Connected Component Labeling Algorithms" In Proceedings of SPIE Medical Imaging Conference, pp. 1965-1976.
- Hanan Samet and Markku Tamminen (1986) "An Improved Approach to connected component labeling of images", International Conference on Computer Vision and Pattern Recognition, pp. 312–318.
- Hanan Samet (1981) "Connected Component Labeling Using Quadtrees", Journal of the ACM - Volume 28, Issue 3, pp. 487 – 501.
- Liu Qing, Tang Linbo, Zhao Baojun, Sun Jingle (2012), "A Fast Target Tracking Algorithm Basted on Connected Component Labeling and Grey Value Statistics", International conference, pp 1267-1270.
- He, L. , Chao, Y. , Suzuki, K. (2007), "A Linear-Time Two-Scan Labeling Algorithm", IEEE International Conference on Image Processing, vol. 5, PP. 241–244.
- Computer Vision CITS4240 "Binary Images" School of Computer Science & Software Engineering The University of Western Australia.
- Kesheng Wu, Ekow Otoo, Kenji Suzuki, "Optimization Two-Pass Connected Labeling Algorithm" Science of U. S. department of Energy under contract no. DE-AC03-76SF00098.
- Fu Chang, Chun-Jen Chen, and Chi-Jen Lu (2003) "A linear-time component-labeling algorithm using contour tracing technique" Computer Vision and Image Understanding pp. 206-220.
Index Terms
Keywords