Research on Edge Detection Algorithm of Railroad Fastener Image based on FPGA FPGA implementation of an efficient railroad fastener image edge detection algorithm

被引：0
|
作者：
Ning, Keqing [1 ]
Chu, Chongchong [1 ]
Xing, Na [1 ]
Du, Minghua [2 ]
机构：
[1] North China Univ Technol, Beijing 100144, Peoples R China
[2] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 1, Dept Emergency, Beijing 100853, Peoples R China
来源：
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ALGORITHMS, SOFTWARE ENGINEERING, AND NETWORK SECURITY, ASENS 2024 | 2024年
关键词：
Railroad fastener images; FPGA; Improved Canny algorithm; Preprocessing module; Nonmaximum value suppression;
D O I：
10.1145/3677182.3677234
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Most of the railroad fastener images have the problems of low contrast, complex image noise and difficult to recognize edge details.For these difficult problems, this paper improves the traditional Canny algorithm by using a hybrid filter composed of adaptive median filter and Gaussian filter to preprocess the image; improves the Sobel operator by using 5*5 eight-direction templates instead of the traditional 3*3 four-direction templates, and expands the computational direction of the non-maximum value suppression module to eight directions.The experimental results show that the improved algorithm has better image edge detection performance on FPGA, lower resource utilization and faster image processing.
引用
收藏
页码：290 / 295
页数：6
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