FORWARD DIFFERENCE EDGE DETECTOR BASED ON FPGA IMPLEMENTATION

Authors

  • Shatha AbuShanab -Department of Computer Systems Engineering, Faculty of Engineering and Technology, Palestine Technical University – Kadoorie (PTUK), Palestine https://orcid.org/0000-0002-8550-5301

DOI:

https://doi.org/10.11113/aej.v16.24274

Keywords:

Edge Detection, FPGA, low power design, vhdl

Abstract

This paper aims to develop and implement the forward difference edge detector on different Field Programmable Gate Array (FPGA) technologies. It investigates how different CMOS technologies influence the power dissipated by digital design. Digital design in terms of low power has become a very challenging problem. Recently, FPGAs, which are semiconductor devices, have been targeted for image processing applications to reduce the computational times needed due to their parallelism techniques. The forward difference algorithm is developed at a high level of abstraction and is performed using physical instruments to obtain real data that is valuable and essential. ModelSim Altera and Quartus Intel are used to describe the algorithm, selecting the VHDL language. The digital design for the forward difference edge detector is completely implemented and verified on Cyclone IV, Cyclone V, and Cyclone LP 10 FPGA devices. At the hardware level, more information is obtainable to estimate the power dissipation correctly. The results indicate CMOS technologies used can be determined based on the design specifications and their power dissipation.

References

W. Burger and M. J. Burge, 2022. Digital image processing: An algorithmic introduction. Cham, Switzerland: Springer.

R. C. Gonzalez and R. E. Woods, 2018. Digital image processing. New York, New York: Pearson Education, [Online]. Available: https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=5832133 4th Edition, Pearson Education, New York.

A. Dehghani, A. Kavari, M. Kalbasi, and K. RahimiZadeh, 2022. "A new approach for design of an efficient FPGA-based reconfigurable convolver for image processing," (in En;en), The Journal of Supercomputing 78(2): 2597–2615, DOI: 10.1007/s11227-021-03963-6.

A. Metkar, M. Maroo, A. Sawant, V. Singh, and S. Mhatre, 2020. Hardware Implementation of Image Processing Algorithms on FPGA, In Proceedings of the 3rd International Conference on Advances in Science & Technology (ICAST).

Farhanaaz and V. Sanju, "Field Programmable Gate Array(FPGA): An Innovation In Hardware Technology," in 2023 2nd International Conference for Innovation in Technology (INOCON) Bangalore, India, 1–6. DOI: 10.1109/INOCON57975.2023.10101210

J. Ruiz-Rosero, G. Ramirez-Gonzalez, and R. Khanna, 2019. "Field Programmable Gate Array Applications—A Scientometric Review," Computation, 7(4): 63. DOI: 10.3390/computation7040063.

P. Babu and E. Parthasarathy, "Reconfigurable FPGA Architectures: A Survey and Applications," Journal of The Institution of Engineers (India): Series B 102(1): 143–156, 2021, DOI: 10.1007/s40031-020-00508-y.

D. G. Bailey, 2024. Design for embedded image processing on FPGAs. Hoboken, NJ: John Wiley & Sons Inc

T. Jagadesh, "Implementation of Prewitt Operator based Edge Detection Algorithm using FPGA," International Journal for Research in Applied Science and Engineering Technology 8(5): 1078–1082, 2020, DOI: 10.22214/ijraset.2020.5171.

G. Ravivarma, K. Gavaskar, D. Malathi, K. G. Asha, B. Ashok, and S. Aarthi, 2021, "Implementation of Sobel operator based image edge detection on FPGA," Materials Today: Proceedings, 45: 2401–2407. DOI: 10.1016/j.matpr.2020.10.825.

L. Xu and D. Zheng, 2022, "A Novel Sobel Edge Detection Accelerator Based on Reconfigurable Architecture," Traitement du Signal. 39(4): 1421–1427. DOI: 10.18280/ts.390436.

Z. I. Azhari, S. Setumin, E. Noorsal, and M. H. Abdullah, 2023. Digital image enhancement by brightness and contrast manipulation using Verilog hardware description language. International Journal of Electrical and Computer Engineering, 13(2), 1346-1357. DOI: 10.11591/ijece.v13i2.

[13] A. G. Mahalle and A. M. Shah, 2017. " FPGA Implementation of Gradient Based Edge Detection Algorithms," International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE), 5(5)

M. Orthy, S. M. R. Islam, F. Rashid, and M. A. Hasan, 2023, "Implementation of Image Enhancement and Edge Detection Algorithm on Diabetic Retinopathy (DR) Image Using FPGA," IET Circuits, Devices & Systems, 2023, 1: 1–12, DOI: 10.1049/2023/8820773.

Z. N. Khudhair et al., 2023. "Color to Grayscale Image Conversion Based on Singular Value Decomposition," IEEE Access, 11: 54629–54638, doi: 10.1109/ACCESS.2023.3279734.

"Mixed-signal generator module:Design and Verification in MATLAB and Verilog hardware description language," International Journal of Emerging Trends in Engineering Research, 8(9): 5064–5069, 2020, DOI: 10.30534/ijeter/2020/28892020.

A. S. Karnea and S. S. Navalgunda, 2013mplementation of an image thinning algorithm using Verilog and MATLAB, " International Journal of Current Engineering and Technology, (Ncwse), 333-337.

[18] P. G. Patel, A. Ahmadi, and M. Khalid, 2021. "Implementing An Improved Image Enhancement Algorithm On FPGA," In 2021 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 1-6. DOI: 10.1109/CCECE53047.2021.9569049.

S. AbuShanab, 2018. "Remote and on-site laboratory system for low-power digital circuit design," Ph.D. thesis, Siegen. https://nbn-resolving.org/urn:nbn:de:hbz:467-13459. (accessed: Jan. 5, 2025).

[20] A. Schwandt and M. Winzker, 2023. "Virtual Mobility for All with the FPGA Vision Open Online Course," In International Conference on Remote Engineering and Virtual Instrumentation, 703-714. Cham: Springer Nature Switzerland. DOI: 10.1007/978-3-031-42467-0_66.

S. AbuShanab, M. Winzker, and R. Bruck, 2015. "Remote low-power digital design system," in 2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT). 1–6.

Altera: Cyclone® IV Featured Documentation - Quick Links Guide. https://www.intel.com/content/www/us/en/docs/programmable/767845/current/cyclone-iv-featured-documentation-quick.htm (accessed: Jan. 5, 2025).

Altera: Cyclone® V Device Datasheet, 5CEBA2F17C6. https://www.datasheets360.com/part/detail/5ceba2f17c6/4718592257345144063/. (accessed: Jan. 5, 2025).

Altera: Cyclone® 10 LP Device Overview. https://www.intel.com/content/www/us/en/docs/programmable/683879/current/device-overview.html. (accessed: Jan. 5, 2025).

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Published

2026-03-01

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