Paper Info
Title
Parallel Algorithms for Edge Detection in an Image
Abstract
Edge detection is an important process in image segmentation, object recognition, template matching, etc. It computes gradients in both horizontal and vertical directions of the image at each pixel position to find the image boundaries. The conventional edge detectors take significant time to detect the edges in the image. To reduce the computational time, this paper proposes parallel algorithms for edge detection with Sobel, Prewitt and Robert first order derivatives using a Shared Memory - Single Instruction Multiple Data (SM - SIMD) parallel architecture. From the experimental results, it is inferred that the proposed parallel algorithms for edge detection are faster than the conventional methods.
Year
DOI
Venue
2014
10.1109/NBiS.2014.15
Network-Based Information Systems
Keywords
Field
DocType
edge detection,image matching,image segmentation,object recognition,parallel algorithms,parallel architectures,shared memory systems,Prewitt first order derivatives,Robert first order derivatives,SM-SIMD parallel architecture,Sobel first order derivatives,edge detection,edge detectors,image boundaries,image horizontal direction,image segmentation,image vertical direction,object recognition,parallel algorithm,shared memory-single instruction multiple data,template matching,Convolution,Derivative,Edge detector,Parallelism,Segmentation
Computer vision,Canny edge detector,Image gradient,Deriche edge detector,Feature detection (computer vision),Computer science,Edge detection,Sobel operator,Artificial intelligence,Morphological gradient,Prewitt operator
Conference
Citations 
PageRank 
References 
0
0.34
4
Authors
2
Name
Order
Citations
PageRank
C. Mala1259.19
M. Sridevi2165.07