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Image Mosaicing Using Binary Edge Detection Algorithm in a Cloud-Computing Environment

Image Mosaicing Using Binary Edge Detection Algorithm in a Cloud-Computing Environment

Abdullah Alamareen, Omar Al-Jarrah, Inad A. Aljarrah
Copyright: © 2018 |Pages: 15
ISBN13: 9781522556497|ISBN10: 1522556494|EISBN13: 9781522556503
DOI: 10.4018/978-1-5225-5649-7.ch008
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MLA

Alamareen, Abdullah, et al. "Image Mosaicing Using Binary Edge Detection Algorithm in a Cloud-Computing Environment." Fog Computing: Breakthroughs in Research and Practice, edited by Information Resources Management Association, IGI Global, 2018, pp. 183-197. https://doi.org/10.4018/978-1-5225-5649-7.ch008

APA

Alamareen, A., Al-Jarrah, O., & Aljarrah, I. A. (2018). Image Mosaicing Using Binary Edge Detection Algorithm in a Cloud-Computing Environment. In I. Management Association (Ed.), Fog Computing: Breakthroughs in Research and Practice (pp. 183-197). IGI Global. https://doi.org/10.4018/978-1-5225-5649-7.ch008

Chicago

Alamareen, Abdullah, Omar Al-Jarrah, and Inad A. Aljarrah. "Image Mosaicing Using Binary Edge Detection Algorithm in a Cloud-Computing Environment." In Fog Computing: Breakthroughs in Research and Practice, edited by Information Resources Management Association, 183-197. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5649-7.ch008

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Abstract

Image Mosaicing is an image processing technique that arises from the need of having a more realistic view of the real world wider than the view captured by the lenses of the available cameras. In this paper, a sequence of images will be mosaiced using binary edge detection algorithm in a cloud-computing environment to improve processing speed and accuracy. The authors have used Platform as a Service (PaaS) to provide a number of nodes in the cloud to run the computational intensive image processing and stitching algorithms. This increased the processing speed as most of image processing algorithms deal with every single pixel in the image. Message Passing Interface (MPI) is used for message passing among the compute-nodes in the cloud and a MapReduce technique is used for image distribution and collection, where the root node is used as reducer and the others as mappers. After applying the algorithm on different sequence of images and different machines on JUST cloud, the authors have achieved high mosaicing accuracy, and the execution time has been improved when comparing it with sequential execution on the images.

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