DocumentCode :
2997480
Title :
Edge detection of decayed wood image based on mathematical morphological double gradient algorithm
Author :
Wang, Xueshun ; Qi, Dawei ; Li, Yuanxiang
fYear :
2008
fDate :
1-3 Sept. 2008
Firstpage :
1226
Lastpage :
1231
Abstract :
Mathematical morphology is a new subject established based on rigorous mathematical theories. In the basis of set theory, mathematical morphology is used for image processing, analysing and comprehending. It is a powerful tool in the geometric morphological analysis and description. Based on the study of mathematical morphology, a new mathematical morphological double-gradient algorithm is proposed, and it is used in edge detection of decayed wood images. Structuring elements are chose appropriately, in order to suppress noises and be adapted to different edges of images. Mathematical morphological double gradient algorithm is constructed by weight adding combination of morphological operation. The results of simulation in decayed wood image processing demonstrate that the method performs better in noise-suppression and edge detection than conventional edge detection operations. Consequently, it provides a new method in processing decayed wood images.
Keywords :
computational geometry; edge detection; gradient methods; image denoising; mathematical morphology; set theory; wood processing; decayed wood image processing; double gradient algorithm; edge detection; geometric morphological analysis; geometric morphological description; image noise suppression; mathematical morphology; set theory; Arithmetic; Automation; Forestry; Image edge detection; Image processing; Morphology; Multi-stage noise shaping; Set theory; Shape; Skeleton; Edge detection; Image processing; Mathematical morphology; wood nondestructive detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-2502-0
Electronic_ISBN :
978-1-4244-2503-7
Type :
conf
DOI :
10.1109/ICAL.2008.4636339
Filename :
4636339
Link To Document :
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