EconPapers    
Economics at your fingertips  
 

Adaptive Mixed Edge Detection of Furnace Flame Image

Chen Peng (), Chuanliang Cheng () and Ling Wang ()
Additional contact information
Chen Peng: Shanghai University, School of Mechatronic Engineering and Automation
Chuanliang Cheng: Shanghai University, School of Mechatronic Engineering and Automation
Ling Wang: Shanghai University, School of Mechatronic Engineering and Automation

Chapter Chapter 2 in Reconstruction and Intelligent Control for Power Plant, 2023, pp 23-37 from Springer

Abstract: Abstract EdgeFurnace detection is one of the major research field in image processing. Through edge detection, the target area and background area can be effectively divided. Besides, the contour and shape of the target area can also be obtained, which provides a basis for calculating the centroid and other important position parameters of the target area. However, due to the complexity of the furnaceFurnace environment in coal-fired power plantsCoal-fired power plant, the existing edge detection algorithms generally can not be directly used to deal with discontinuous edges, coarse edges, false edges, etc.

Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-19-5574-7_2

Ordering information: This item can be ordered from
http://www.springer.com/9789811955747

DOI: 10.1007/978-981-19-5574-7_2

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-05-20
Handle: RePEc:spr:sprchp:978-981-19-5574-7_2