FPGA implementation of image edge detection based on four algorithms of GAUSS-filter, SOBEL, NMS and OTSU

张灏,; Zhang, Hao; 王素珍,; Wang, Shuzhen; 郑宇,; Zheng, Yao; 王伟,; Wang, Wei; 李潍志,; Li, Weizhi; 王鹏,; Wang, Peng; 任贵珊,; Ren, Guanghui; 马家麟,; Ma, Jialin

doi:10.3788/yjyxs20203503.0250

Cited by 6 publications

(2 citation statements)

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“…The detailed description of the proposed Canny edge detection algorithm is given below. Here, we use the Sobel operator [12][13] as a gradient mask. There is significant motivation for employment of the Sobel operator rather than other operators used in [10,11] because it combines differentiation and Gaussian smoothing.…”

Section: Improved Canny Edge Detection Algorithmmentioning

confidence: 99%

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FPGA implementation of a real-time edge detection system based on an improved Canny algorithm

Guo

2022

Preprint

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Canny edge detection is one of the most widely used edge detection algorithms due to its superior performance. However, it is complex, time-consuming process and has a high hardware cost. In addition, most of the existing implementations of the algorithm use the same fixed pair of high and low threshold values for all input images. This cannot automatically adapt to changes in the external detection environment and results in decreased performance. To overcome these issues, an improved Canny algorithm is proposed in this paper. It uses the Sobel operator and approximation methods to calculate the gradient magnitude and direction for replacing complex operations with reduced hardware cost. Otsu’s algorithm is introduced to adaptively determine the image threshold. However, Otsu’s algorithm has division operations,and the division operation is complex, has low efficiency and slow speed. We introduce a logarithmic unit to turn division into a subtraction operation that is easy to implement by hardware but which does not affect the selection of the threshold. Experimental results show that the system can detect the edge of the image well without adjusting the threshold value when the external environment changes and requires only 1.231 ms to detect the edges of the 512 x 512 image when clocked at 50 MHz. Compared with existing FPGA implementations, our implementation uses the least amount of logical resources. Thus, it is more suitable for platforms have limited logical resources.

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Section: Improved Canny Edge Detection Algorithmmentioning

confidence: 99%

“…For Eq. ( 3), we use the addition of the absolute values of 𝑓 𝑥 (𝑥, 𝑦) and 𝑓 𝑦 (𝑥, 𝑦) , which are presented in [12,13], to find the gradient magnitude mag (x, y). Eq.…”

Section: Low Complexity Gradient Magnitude and Direction Calculationmentioning

confidence: 99%

FPGA implementation of a real-time edge detection system based on an improved Canny algorithm

Guo

2022

Preprint

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An Edge Detection Algorithm of Noisy Image Based on OTSU Adaptive Threshold Segmentation

Wang,

Lin,

Zhang

2024

2024 Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)

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Safety Helmet Recognition Video Surveillance System Based on SSD Target Detection Algorithm

范¹

2021

JSST

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FPGA implementation of image edge detection based on four algorithms of GAUSS-filter, SOBEL, NMS and OTSU

Cited by 6 publications

References 0 publications

FPGA implementation of a real-time edge detection system based on an improved Canny algorithm

FPGA implementation of a real-time edge detection system based on an improved Canny algorithm

An Edge Detection Algorithm of Noisy Image Based on OTSU Adaptive Threshold Segmentation

Safety Helmet Recognition Video Surveillance System Based on SSD Target Detection Algorithm

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