UPSI Digital Repository (UDRep)
|
UPSI Digital Repository (UDRep)
|
|
|
| ||||||||||||||||||||||||
| Abstract : Universiti Pendidikan Sultan Idris |
| Choosing a quality image is the goal of image processing of two-dimensional (2D) images through computer vision. Image processing consists of stages, namely acquisition, pre-processing (enhancement), segmentation, representation and description, as well as introduction and interpretation. Edge detection is a stage in image processing that aims to find the pattern of an image. This study analyzes the quality of 2D images through edge detection techniques with a comparison of various techniques and error analysis. The comparison of edge detection in this study was performed on images produced using some techniques, such as Canny, Sobel, Prewitt, and Roberts. To analyze the error, Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) were used. This study was conducted using Matlab by comparing six different images of lung, car, leaf, apple, cat, and motorcycle. The results show that using edge detection with the Canny technique may result in the best MSE and PSNR values. Consistent results of six images detected also show that Canny technique produced the best MSE and PSNR values among the results produced by the Sobel, Prewitt, and Roberts techniques. (2023), (International Association of Engineers). All Rights Reserved. |
| References |
Jie Yanga ,Ran Yanga, Shigao Lib,S.Shoujing Yina, Qianqing Qina,” A Novel Edge Detection Based Segmentation Algorithm for Polarimetric Sar Images”, The International Archives of the Photogrammetry, Remote sensing and Spatial Information,Sciences. Vol. XXXVII, Part B7. Beijing 2008. Khairudin, M.,Yusuf, D.M.,Yatmono, S.,Azman, M.N.A.,Asmara, A. Fuzzy logic based on image processing to control a dc motor. Journal of Physics: Conference Series 1833 (1). 2021 Orlando, J, Tobias & Rui Seara (2002) “Image Segmentation by Histogram Thresholding Using Fuzzy Sets”, IEEE Transactions on Image Processing, Vol.11, No.12, 1457-1465. Punam Thakare (2011) “A Study of Image Segmentation and Edge Detection Techniques” International Journal on Computer Science and Engineering, Vol 3, No.2, 899-904. Khairudin, M.,Chen, G.D.,Wu, M.C.,Asnawi, R.,Nurkhamid. Control of a movable robot head using vision-based object tracking. International Journal of Electrical and Computer Engineering Vol.9 No.4, pp.2503. 2019 Jianlun Wang, Jianlei He, Yu Han, Changqi Ouyang, DaoliangLi. An Adaptive Thresholding algorithm of field leaf image. Computers and Electronics in Agriculture. Vol. 96, Aug 2013, pp 23-39. https://doi.org/10.1016/j.compag.2013.04.014 Yu, X, Bui, T.D. & et al. (1994) “Robust Estimation for Range Image Segmentation and Reconstruction”, IEEE trans. Pattern Analysis and Machine Intelligence, Vo. 16 No. 5, 530-538. Lakshmi,S & V. Sankaranarayanan (2010) “A Study of edge detection techniques for segmentation computing approaches”, Computer Aided Soft Computing Techniques for Imaging and Biomedical Applications, 35-41. Khairudin, M.,Refalda, R.,Yatmono, S.,Pramono, H.S.,Triatmaja, A.K.,Shah, A. The mobile robot control in obstacle avoidance using fuzzy logic controller. Indonesian Journal of Science and Technology, 5 (3), pp.334. 2020. R. Janani, and T. Ramachandran, "On Relatively Prime Edge Labeling of Graphs," Engineering Letters, vol. 30, no.2, pp659-665, 2022 Canny, J. F (1986) “A computational approach to edge detection”, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol.8, 679-714. S.F. Abdullah, A.F.N.A Rahman, Z.A. Abas, W.H.M. Saad, 2016, Multilayer Perceptron Neural Network in Classifying Gender using Fingerprint Global Level Features, Indian Journal of Science and Technology, Vol 9(9), DOI: 10.17485/ijst/2016/v9i9/84889 Khairudin, M.,Yatmono, S.,Nugraha, A.C.,Ikhsani, M.,Shah, A.,Hakim, M.L. Object Detection Robot Using Fuzzy Logic Controller through Image Processing. Journal of Physics: Conference Series 1737 (1).2021. Gran Badshah, Siau-ChuinLiew, JasniMohd Zain, Mushtaq Ali, 2016, Watermark Compression in Medical Image Watermarking Using Lempel-Ziv-Welch (LZW) Lossless Compression Technique, Journal of Digital Imaging, ISSN: 0897-1889 (Print) 1618-727X (Online), Springer Wahyu Supriyatin. Perbandingan Metode Sobel, Prewitt, Robert dan Canny pada Deteksi Tepi Objek Bergerak. ILKOM Jurnal Ilmiah. Vol. 12 No. 2, Agustus 2020, pp.112-120 Khairudin, M.,Herlambang, S.P.,Karim, H.I.,Azman, M.N.A. Visionbased mobile robot navigation for suspicious object monitoring in unknown environments. Journal of Engineering Science and Technology. Vol.15, No.1, pp.152. 202 S.K. Katiyar, P.V. Arun. Comparative analysis of common edge detection techniques in context of object extraction. IEEE TGRS Vol.50 no.11b. 2014. G.T. Shrivakshan. A Comparison of various Edge Detection Techniques used in Image Processing. IJCSI International Journal of Computer Science Issues, Vol. 9, No. 5, Sept 2012. 269-276 Sujeet Das. Comparison of Various Edge Detection Technique. International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.9, No.2 (2016), pp.143-158 http://dx.doi.org/10.14257/ijsip.2016.9.2.13 Mamta Joshi, Ashutosh Vyas. Comparison of Canny edge detector with Sobel and Prewitt edge detector using different image formats. International Journal of Engineering Research & Technology (IJERT). Vol 2, Issue 3, 2018, pp.133-137 Chinu and Amit Chhabra. Overview and Comparative Analysis of Edge Detection Techniques in Digital Image Processing. International Journal of Information & Computation Technology. Vol. 4, No. 10 (2014), pp. 973-980. Dongqiao Bai, Jikun Tian, Ding Li, and Shouzhi Li, "Multiple UAVs Tracking for Moving Ground Target," Engineering Letters, vol. 30, no.2, pp829-834, 2022 Xinyi Hu, Yunpeng Wang. 2022. Monitoring coastline variations in the Pearl River Estuary from 1978 to 2018 by integrating Canny edge detection and Otsu methods using long time series Landsat dataset. CATENA. Vol. 209, No. 2, Feb 2022, 105840. https://doi.org/10.1016/j.catena.2021.105840 Takeshi R.Fujimoto, Taro Kawasaki, Keiichi Kitamura. Canny-EdgeDetection/Rankine-Hugoniot-conditions unified shock sensor for inviscid and viscous flows. Journal of Computational Physics. Vol.396, No. 1, Nov 2019, Pp 264-279. https://doi.org/10.1016/j.jcp.2019.06.071 Uche A. Nnolim. Automated crack segmentation via saturation channel thresholding, area classification and fusion of modified level set segmentation with Canny edge detection. Heliyon. Vol. 6, No. 12, Dec 2020, pp. 1-16. e05748. https://doi.org/10.1016/j.heliyon.2020.e05748 Kumar Gaurav, Umesh Ghanekar. Image steganography based on Canny edge detection, dilation operator and hybrid coding. Journal of Information Security and Applications. Vol. 41, Aug 2018, Pp 41-51. https://doi.org/10.1016/j.jisa.2018.05.001 Haibin Di, Dengliang Gao. Gray-level transformation and Canny edge detection for 3D seismic discontinuity enhancement. Computers & Geosciences. Vol. 72, Nov 2014, Pp 192-200. https://doi.org/10.1016/j.cageo.2014.07.011 Pinaki pratim acharjya, ritaban das & dibyendu Ghoshal. Study and comparison of different edge detectors for image segmentation. Global Journal of Computer Science and Technology Graphics & Vision. Vol. 12 No. 13 Version 1.0 Year 2012. Youcun Lu, Lin Duanmu, Zhiqiang (John) Zhai, Zongshan Wang, Application and improvement of Canny edge-detection algorithm for exterior wall hollowing detection using infrared thermal images, Energy and Buildings, vol. 274, 2022, 112421, https://doi.org/10.1016/j.enbuild.2022.112421. |
| This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials. You may use the digitized material for private study, scholarship, or research. |