The original catenary image may include noise or have low brightness, which makes the image quality low. On the one hand, the catenary is installed in the natural environment for a long time and is easily affected by the dirt in the environment. The catenary components in the tunnel are also vulnerable to the long-term impact of tunnel dust. It causes their state characteristics to be submerged by noise and interference, which will increase the detection difficulty. In addition, in the process of receiving, transmitting, and processing, the image will also be affected by noise such as electromagnetic interference of the sensor, resulting in a decline in image quality and affecting the detection accuracy.
Preprocessing of Catenary Support Components’ Images
Advances High-speed Rail
Deep Learning-Based Detection of Catenary Support Component Defect and Fault in High-Speed Railways ; Kapitel : 4 ; 55-94
11.04.2023
40 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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