Artificial bee colony algorithm for enhancing image edge detection

2018 ◽  
Vol 10 (4) ◽  
pp. 679-687 ◽  
Author(s):  
Anan Banharnsakun
Author(s):  
Tapan Sharma ◽  
Vinod Shokeen ◽  
Sunil Mathur

The remote sensing domain has witnessed tremendous growth in the past decade, due to advancement in technology. In order to store and process such a large amount of data, a platform like Hadoop is leveraged. This article proposes a MapReduce (MR) approach to perform edge detection of satellite images using a nature-inspired algorithm Artificial Bee Colony (ABC). Edge detection is one of the significant steps in the field of image processing and is being used for object detection in the image. The article also compares two edge detection approaches on Hadoop with respect to scalability parameters such as scaleup and speedup. The experiment makes use of Amazon AWS Elastic MapReduce cluster to run MR jobs. It focuses on traditional edge detection algorithms like Canny Edge (CE) and the proposed MR based Artificial Bee Colony approach. It observes that for five images, the scaleup value of CE is 1.1 whereas, for MR-ABC, it is 1.2. Similarly, speedup values come out to be 1.02 and 1.04, respectively. The algorithm proposed by authors in this article scales comparatively better when compared to Canny Edge.


2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Dujin Liu ◽  
Huajun Wang ◽  
Sen Wang ◽  
Guolin Pu ◽  
Xiaoya Deng ◽  
...  

As the color remote sensing image has the most notable features such as huge amount of data, rich image details, and the containing of too much noise, the edge detection becomes a grave challenge in processing of remote sensing image data. To explore a possible solution to the urgent problem, in this paper, we first introduced the quaternion into the representation of color image. In this way, a color can be represented and analyzed as a single entity. Then a novel artificial bee colony method named improved artificial bee colony which can improve the performance of conventional artificial bee colony was proposed. In this method, in order to balance the exploration and the exploitation, two new search equations were presented to generate candidate solutions in the employed bee phase and the onlookers phase, respectively. Additionally, some more reasonable artificial bee colony parameters were proposed to improve the performance of the artificial bee colony. Then we applied the proposed method to the quaternion vectors to perform the edge detection of color remote sensing image. Experimental results show that our method can get a better edge detection effect than other methods.


2019 ◽  
Vol 6 (3) ◽  
pp. 179-194
Author(s):  
Ricardo Contreras Arriagada ◽  
Ricardo Contreras Apablaza ◽  
Maria Angélica Pinninghoff

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