Open Access
Issue |
MATEC Web of Conferences
Volume 150, 2018
Malaysia Technical Universities Conference on Engineering and Technology (MUCET 2017)
|
|
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Article Number | 06029 | |
Number of page(s) | 6 | |
Section | Information & Communication Technology (ICT), Science (SCI) & Mathematics (SM) | |
DOI | https://doi.org/10.1051/matecconf/201815006029 | |
Published online | 23 February 2018 |
- S. E. Umbaugh, Digital image processing and analysis: human and computer vision applications with CVIPtools, Second Edi. CRC Press, 2010. [Google Scholar]
- L. Mulrane, E. Rexhepaj, S. Penney, J. J. Callanan, and W. M. Gallagher, “Automated image analysis in histopathology: a valuable tool in medical diagnostics”, Expert Rev. Mol. Diagn., vol. 8, no. 6, pp. 707–725, Nov. 2008. [CrossRef] [Google Scholar]
- H. Zhou, H. Kong, L. Wei, D. Creighton, and S. Nahavandi, “On Detecting Road Regions in a Single UAV Image”, IEEE Trans. Intell. Transp. Syst., vol. 18, no. 7, pp. 1713–1722, 2016. [CrossRef] [Google Scholar]
- M. A. M. Abdullah, S. S. Dlay, W. L. Woo, and J. A. Chambers, “Robust Iris Segmentation Method Based on a New Active Contour Force With a Noncircular Normalization” IEEE Trans. Syst. Man, Cybern. Syst., pp. 1–-14, 2016. [Google Scholar]
- [5]P. Smith, D. B. Reid, C. Environment, L. Palo, P. Alto, and P. L. Smith, “Otsu1975,” vol. 20, no. 1, pp. 62–66, 1979. [Google Scholar]
- A. Lucieer, D. Turner, D. H. King, and S. A. Robinson, “Using an Unmanned Aerial Vehicle (UAV) to capture micro-topography of Antarctic moss beds”, Int. J. Appl. Earth Obs. Geoinf., vol. 27, pp. 53–62, Apr. 2014. [CrossRef] [Google Scholar]
- T. Y. Lim and M. M. Ratnam, “Edge detection and measurement of nose radii of cutting tool inserts from scanned 2-D images”, Opt. Lasers Eng., vol. 50, no. 11, pp. 1628–1642, Nov. 2012. [CrossRef] [Google Scholar]
- J. Huang, X. You, Y. Y. Tang, L. Du, and Y. Yuan, “A novel iris segmentation using radial-suppression edge detection”, Signal Processing, vol. 89, no. 12, pp. 2630–2643, 2009. [CrossRef] [Google Scholar]
- S. a. Coleman, B. W. Scotney, and S. Suganthan, “Multi-scale edge detection on range and intensity images”, Pattern Recognit., vol. 44, no. 4, pp. 821–838, Apr. 2011. [CrossRef] [Google Scholar]
- W. H. W. He and K. Y. K. Yuan, An improved Canny edge detector and its realization on FPGA. Ieee, 2008, pp. 6561–6564. [Google Scholar]
- S. B. Kutty, S. Saaidin, P. N. A. Megat Yunus, and S. Abu Hassan, “Evaluation of canny and sobel operator for logo edge detection”, ISTMET 2014 - 1st Int. Symp. Technol. Manag. Emerg. Technol. Proc., vol. 2, no. Istmet, pp. 153–156, 2014. [CrossRef] [Google Scholar]
- Z. Othman, A. Abdullah, and A. S. Prabuwono, “A statistical Approach of Multiple Resolution Levels for Canny Edge Detection”, in Intelligent Systems Design and Applications (ISDA), 2012, 2012, pp. 837–841. [CrossRef] [Google Scholar]
- Z. Othman and A. Abdullah, “An Adaptive Threshold Based On Multiple Resolution Levels for Canny Edge Detection”, in IRICT 2017: Recent Trends in Information and Communication Technology, 2017, pp. 316–323. [Google Scholar]
- W. Gao, L. Yang, X. Zhang, and H. Liu, “An improved Sobel edge detection”, Proc. - 2010 3rd IEEE Int. Conf. Comput. Sci. Inf. Technol. ICCSIT 2010, vol. 5, pp. 67–71, 2010. [Google Scholar]
- J. Canny, “A computational approach to edge detection.”, IEEE Trans. Pattern Anal. Mach. Intell., vol. 8, no. 6, pp. 679–98, Jun. 1986. [CrossRef] [Google Scholar]
- B. Wang and S. Fan, “An improved CANNY edge detection algorithm Bing”, 2009 Second Int. Work. Comput. Sci. Eng., 2009. [Google Scholar]
- G. Jie and L. Ning, “An Improved Adaptive Threshold Canny Edge Detection Algorithm”, 2012 Int. Conf. Comput. Sci. Electron. Eng., pp. 164–168, Mar. 2012. [CrossRef] [Google Scholar]
- Nasruddin Abu Sari, Asmala Ahmad, MY Abu Sari, S Sahib, AW Rasib (2015) Development Of Rapid Low-Cost LARS Platform For Oil Palm Plantation. Jurnal Teknologi, 77 (20), 99 – 105 (Scopus). EISSN 2180-3722. [Google Scholar]
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