Title :
An improved canny edge detection application for asphalt concrete
Author :
Agaian, Sos ; Almuntashri, Ali ; Papagiannakis, A.T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Texas at San Antonio, San Antonio, TX, USA
Abstract :
In this paper we introduce an improved Canny edge detection algorithm and an edge preservation filtering procedure for asphalt concrete (AC) applications. Datasets of AC images were randomly selected to test this algorithm. Computer simulations show that the improved algorithm can make up for the disadvantages of Canny algorithm, detect edges of AC images effectively, and is a less time-consuming process. Particularly, it has been shown that the presented algorithm can not only eliminate noises effectively but also protect unclear edges.
Keywords :
asphalt; concrete; edge detection; filtering theory; image fusion; image segmentation; production engineering computing; AC image dataset; asphalt concrete; edge preservation filtering; image fusion; image segmentation; improved Canny edge detection; Aggregates; Application software; Asphalt; Computed tomography; Concrete; Filtering; Image edge detection; Image processing; Image segmentation; X-ray imaging; Asphalt concrete; Canny operator; edge detection; gradient vector; image fusion; image segmentation;
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
DOI :
10.1109/ICSMC.2009.5346873
