Open AccessEdge Detection using Distinct Particle Swarm Optimization
Author(s) -
Naveen Singh Dagar,
Pawan Kumar Dahiya
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.h7259.078919
Subject(s) - canny edge detector , deriche edge detector , image gradient , artificial intelligence , edge detection , particle swarm optimization , computer vision , sobel operator , computer science , enhanced data rates for gsm evolution , pixel , precision and recall , pattern recognition (psychology) , prewitt operator , ground truth , mathematics , image (mathematics) , image processing , algorithm
Edge detection is long-established in computer perception approach such as object detection, shape matching, medical image classification etc. For this reason many edge detectors like, Sobel, Robert, Prewitt, Canny etc. has been progressed to increase the effectiveness of the edge pixels. All these approaches work fine on images having minimum variation in intensity. Therefore, a new objective function based distinct particle swarm optimization (DPSO) is proposed in this paper to identify unbroken edges in an image. The conventional edge detectors such as “Canny” & computational intelligent techniques like ACO, GA and PSO are compared with proposed algorithm. Precision, Recall & F-Score is used as performance parameters for these edge detection techniques. The ground truth images are taken as reference edge images and all the edge images acquired by different edge detection systems are contrasted with reference edge image with ascertain the Precision, Recall and F-Score. The techniques are tested on 500 test images from the “BSD500” datasets. The empirical results presented by the proposed algorithm performance better than other edge detection techniques in the images. The proposed method observes edges more accurately and smoothly than other edge detection techniques such as “Canny, ACO, GA and PSO” in different images