VLSI Architecture for Edge Detection of Leaf Images

This paper proposed a new VLSI Architecture for Sobel Edge detector for Cotton and Grape leaf images. This new VLSI Architecture is tested for leaf images using Verilog HDL and Simulated and Synthesized using Xilinx Vivado tool and results shown the low power and low area, utilized less than 0.01% of LUTs and 0.13 w of power only. The same architecture is also extended for Prewitt and Laplace Edge detectors and results shown that utility of power and area is less.

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Publication Details

Journal
Transactions on Machine Learning and Artificial Intelligence
Published
2025-04-25
DOI
https://doi.org/10.14738/tmlai.1302.18612
Citations
1
Primary Topic
Leaf Properties and Growth Measurement
Type
article
Field-Weighted Citation Impact
1.75

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article

VLSI Architecture for Edge Detection of Leaf Images

G. Sukanya
1 citations
Transactions on Machine Learning and Artificial Intelligence
Leaf Properties and Growth Measurement
1.75
article

VLSI Architecture for Edge Detection of Leaf Images

G. Sukanya
article en
1 citations

Abstract

This paper proposed a new VLSI Architecture for Sobel Edge detector for Cotton and Grape leaf images. This new VLSI Architecture is tested for leaf images using Verilog HDL and Simulated and Synthesized using Xilinx Vivado tool and results shown the low power and low area, utilized less than 0.01% of LUTs and 0.13 w of power only. The same architecture is also extended for Prewitt and Laplace Edge detectors and results shown that utility of power and area is less.

Transactions on Machine Learning and Artificial IntelligenceVol. 13(02)
Jawaharlal Nehru Technological University, Hyderabad (IN)
All India Council for Technical Education, Jawaharlal Nehru Technological University Hyderabad
Openalex Percentile: Top 15%
Leaf Properties and Growth Measurement
1.75
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VLSI Architecture for Edge Detection of Leaf Images — G. Sukanya · Transactions on Machine Learning and Artificial Intelligence (2025) | TGRS Research Map | TGRS