Research PaperNo Access

ASIC Design of Low Power Sobel Edge Detection Filter: An Analog Approach

Department of Electronics and Communication Engineering, Dr. Mahalingam College of Engineering and Technology, Coimbatore 642003, India

E-mail Address: vijey.tn@gmail.com

Corresponding author.

Search for more papers by this author

Silambarasan Dharmalingam

Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Chennai 602117, India

E-mail Address: simbu.chandran@gmail.com

Search for more papers by this author

Vineel Talluri Jessy

Department of Electronics and Communication Engineering, Dr. Mahalingam College of Engineering and Technology, Coimbatore 642003, India

E-mail Address: Vineeltalluri@gmail.com

Search for more papers by this author

, and

V. Aravind

Department of Electronics and Communication Engineering, Dr. Mahalingam College of Engineering and Technology, Coimbatore 642003, India

E-mail Address: aravindviji15@gmail.com

Search for more papers by this author

https://doi.org/10.1142/S0218126624502013Cited by:0 (Source: Crossref)

Abstract

This paper proposes a novel analog front end to filter edges in captured images. The proposed architecture employs the Sobel algorithm and uses a $3 \times 3$ $3 \times 3$ kernel to process the input images. We used 180 nm Semi-Conductor Laboratory (SCL) CMOS fabrication technology for implementation with a power supply of 1.8 V. The proposed design employs six analog differential pairs in each horizontal and vertical gradient unit. The inputs to the differential pairs are the active signals fed from the $3 \times 3$ $3 \times 3$ kernel using the Sobel weight masks. We connected the differential datum pairs in cascade to estimate the gradient index in horizontal/vertical direction using the net difference current between the output terminals. The horizontal and vertical gradient units, viz., $G_{H}$ $G_{H}$ and $G_{V}$ $G_{V}$ , respectively, are configured based on the polarity of weights in respective Sobel masks. The gradient $(G)$ $(G)$ of the processing pixel (PP) is estimated using the net difference current in the combined circuitry employing $G_{H}$ $G_{H}$ and $G_{V}$ $G_{V}$ cells. The key advantages of the proposed design are very low area realization, high accuracy, and low power dissipation. The efficacy of the proposed edge filter analog front end is estimated through simulations and analysis with two sets of test signals in the processing window.

This paper was recommended by Regional Editor Giuseppe Ferri.

Keywords:

References

1. J. Canny, A computational approach to edge detection, IEEE Trans. Pattern Anal. Mach. Intell. 8 (1986) 679–698. Crossref, Web of Science, Google Scholar
2. N. Kanopoulous, N. Vasanthavada and R. L. Baker, Design of an image edge detection filter using the Sobel operator, IEEE J. Solid-State Circuits 23 (1988) 358–367. Crossref, Google Scholar
3. N. Senthikumaran and R. Rajesh, Edge detection techniques for image segmentation — A survey of soft computing approaches, Int. J. Recent Trends Eng. 1 (2009) 250–254. Google Scholar
4. E. J. Mohammad, M. J. Kadhim, W. I. Hamad and S. Y. Helyel, Study Sobel edge detection effect on the image edges using MATLAB, Int. J. Innovative Res. Sci. Eng. Technol. 3 (2011) 10408–10415. Google Scholar
5. G. Yang and F. Xu, Research and analysis of image edge detection algorithm based on the MATLAB (Advanced in Control Engineering and Information Science), Procedia Eng. 15 (2011) 1313–1318, https://doi.org/10.1016/j.proeng.2011.08.243. Crossref, Google Scholar
6. R. Muthukrishnan and M. Radha, Edge detection techniques for image segmentation, Int. J. Comput. Sci. Inf. Technol. 3 (2011) 259–267. Crossref, Google Scholar
7. G. T. Shrivakshan and C. Chandrasekhar, A comparison of various edge detection techniques used in image processing, Int. J. Comput. Sci. Issues 9 (2012) 269–276. Google Scholar
8. N. K. Suryakant, Edge detection using fuzzy logic in MATLAB, Int. J. Adv. Res. Comput. Sci. Software Eng. 2 (2012) 38–40. Google Scholar
9. J. M. Elham et al., Design study Sobel edge detection, Int. J. Appl. Innovation Eng. Manage. 2 (2013) 248–253. Google Scholar
10. T. Sahoo and S. Pine, Design and simulation of various edge detection techniques using Matlab Simulink, Int. Conf. Signal Processing, Communication, Power and Embedded System (SCOPES) (IEEE, 2016), pp. 1224–1228. Crossref, Google Scholar
11. S. Halder, D. Bhattacharjee, M. Nasipuri and D. K. Basu, A fast FPGA based architecture for Sobel edge detection, Progress in VLSI Design and Test (Springer, 2012), pp. 300–306. Crossref, Google Scholar
12. G. Chaple and R. D. Daruwala, Design of Sobel operator-based image edge detection algorithm on FPGA, Int. Conf. Communication and Signal Processing, Melmaruvathur, India, 3–5 April 2014, pp. 788–792. Google Scholar
13. D. Sangeetha and P. Deepa, FPGA implementation of cost-effective robust Canny edge detection algorithm, J. Real-Time Image Process. 16 (2019) 957–970. Crossref, Google Scholar
14. Z. Tang, L. Huang, X. Zhang and H. Lao, Robust image hashing based on color vector angle and Canny operator, AEU Int. J. Electron. Commun. 70 (2016) 833–841. Crossref, Web of Science, Google Scholar
15. G. N. Chaple, R. D. Daruwala and M. S. Gofane, Comparison of Robert, Prewitt, and Sobel operator-based edge detection methods for real-time uses on FPGA, Int. Conf. Technologies for Sustainable Development (ICTSD), Mumbai, India, 4–6 February 2015, pp. 1–4. Google Scholar
16. Y. Zhang, X. Han, H. Zhang and L. Zhao, Edge detection algorithm of image fusion based on improved Sobel operator, IEEE 3rd Information Technology and Mechatronics Engineering Conference (ITOEC), Chongqing, China, 3–5 October 2017, pp. 457–461. Google Scholar
17. K. Zhang, Y. Zhang, P. Wang, Y. Tian and J. Yang, An improved Sobel edge algorithm and FPGA implementation, Procedia Comput. Sci. 131 (2018) 243–248. Crossref, Google Scholar
18. K. Özkan and Ş. Işık, A novel multi-scale and multi-expert edge detector based on common vector approach, AEU Int. J. Electron. Commun. 69 (2015) 1272–1281. Crossref, Web of Science, Google Scholar
19. N. Nausheen, A. Seal, P. Khanna and S. Halder, An FPGA-based implementation of Sobel edge detection, Microprocess. Microsyst. 56 (2018) 84–91. Crossref, Google Scholar
20. H. Yamasaki and T. Shibata, A high-speed median filter VLSI using floating-gate-MOS-based low-power majority voting circuits, Proc. 31st European Solid-State Circuits Conference (ESSCIRC), Grenoble, France, 12–16 September 2005, pp. 125–128. Google Scholar
21. Y.-C. Hung, S.-H. Shieh and C.-K. Tung, A real-time current-mode CMOS analog median filtering cell for system-on-chip applications, Proc. IEEE Conf. Electron Devices and Solid-State Circuits (EDSSC) (IEEE, 2007), pp. 361–364. Crossref, Google Scholar
22. S. Siskos, Low voltage analog median filter implementation, IEEE Int. Conf. Imaging Systems and Techniques, Thessaloniki, Greece, 1–2 July 2010, pp. 166–170. Google Scholar
23. C. Muñiz-Montero, M. A. R. Salinas, L. A. Villa Vargas, H. M. Lozano, V. H. Ponce-Ponce, L. A. Sánchez-Gaspariano and D. Arellano-Gutiérrez, A compact CMOS Class-AB analog median filter, IEEE Third Latin American Symp. Circuits and Systems (LASCAS) (IEEE, 2012), pp. 1–4. Crossref, Google Scholar
24. W. Jendernalik, G. Blakiewicz, J. Jakusz and S. Szczepański, A nine-input 1.25 mW, 34 ns CMOS analog median filter for image processing in real-time, Analog Integr. Circuits Signal Process. 76 (2013) 233–243. Crossref, Web of Science, Google Scholar
25. H. C. Bandala-Hernandez, J. M. Rocha-Pérez, A. Díaz-Sánchez, J. Lemus-López, H. Vázquez-Leal, A. Díaz-Armendariz and J. Ramírez-Angulo, Weighted median filters: An analog implementation, Integration 55 (2016) 227–231. Crossref, Web of Science, Google Scholar
26. A. Wongjan, A. Julsereewong and T. Junsing, Analog median filtering circuit using CMOS three-input max/min cell, 3rd Int. Conf. Control and Robotics Engineering (ICCRE), Nagoya, Japan, 20–23 April 2018, pp. 155–159. Google Scholar
27. F. Khateb, M. Kumngern, S. B. A. Dabbous and T. Kulej, Low-voltage low-power bulk-driven analog median filter, AEU Int. J. Electron. Commun. 70 (2017) 698–706. Crossref, Google Scholar
28. K. K. Sundaram and V. Ramachandran, Analysis of the coefficients of generalised bilinear transformation in the design of 2-D band-pass and band-stop filters and an application in image processing, Canadian Conference on Electrical and Computer Engineering, Saskatoon, SK, Canada, 1–4 May 2005, pp. 1233–1236. Google Scholar
29. J. Chow, W. Siu, Y. Iwamoto, M. Toia and S. Sonkusale, A multipass spatial and temporal image filtering APS CMOS image sensor, in 49th IEEE International Midwest Symposium on Circuits and Systems, (IEEE, 2006), pp. 624–627. Crossref, Google Scholar
30. D. Colaiuda, A. Leoni, G. Ferri and V. Stornelli, A second order 1.8–1.9 GHz tunable active band-pass filter with improved noise performances, Electronics 11 (2002) 2781. Crossref, Google Scholar