Distributed Approach to Process Satellite Image Edge Detection on Hadoop Using Artificial Bee Colony

2020 ◽  
Vol 11 (2) ◽  
pp. 80-94
Author(s):  
Tapan Sharma ◽  
Vinod Shokeen ◽  
Sunil Mathur
Keyword(s):  
Edge Detection ◽  
Artificial Bee Colony ◽  
Satellite Image ◽  
Detection Algorithms ◽  
Distributed Approach ◽  
Bee Colony ◽  
Image Edge Detection ◽  
Nature Inspired Algorithm ◽  
Canny Edge ◽  
Image Edge

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.

An Improved Edge Detection Algorithm Based on Canny Operator

2013 ◽  
Vol 347-350 ◽  
pp. 3541-3545 ◽  
Author(s):  
Dan Dan Zhang ◽  
Shuang Zhao
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Image Simulation ◽  
Edge Image ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Edge Detection Algorithm

The traditional Canny edge detection algorithm is analyzed in this paper. To overcome the difficulty of threshold selecting in Canny algorithm, an improved method based on Otsu algorithm and mathematical morphology is proposed to choose the threshold adaptively and simultaneously. This method applies the improved Canny operator and the image morphology separately to image edge detection, and then performs image fusion of the two results using the wavelet fusion technology to obtain the final edge-image. Simulation results show that the proposed algorithm has better anti-noise ability and effectively enhances the accuracy of image edge detection.

scholarly journals 3D Image Edge Detection Algorithm for Depth Detection

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3555-3557
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
3 Dimensional ◽  
3D Objects ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
3D Scene ◽  
Edge Recognition

Showing a genuine 3 dimensional (3D) objects with the striking profundity data is dependably a troublesome and cost-devouring procedure. Speaking to 3D scene without a noise (raw image) is another case. With a honed technique for survey profundity measurement can be effortlessly gotten, without requiring any extraordinary instrument. In this paper, we have proposed an edge recognition process in a profundity picture dependent on the picture based smoothing and morphological activities.In this strategy, we have utilized the guideline of Median sifting, which has a prestigious element for edge safeguarding properties. The edge discovery was done dependent on the Canny Edge Detection Algorithm. Along these lines this strategy will help to identify edges powerfully from profundity pictures and add to advance applications top to bottom pictures

Wavelet De-Noising Algorithm Based on OpenCV for Images Edge Detection

2014 ◽  
Vol 989-994 ◽  
pp. 3973-3976
Author(s):  
Yi Fan Ma ◽  
Shu Gui Liu
Keyword(s):  
Edge Detection ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Canny Edge Detection ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
Wavelet Algorithm

Image edge detection is easily affected by noise. Wavelet algorithm can divide the image into low frequency and high frequency. By the processing of high frequency signal and the reconstruction of wavelet coefficients, the purpose of removing noise can be achieved. In the environment of VC++6.0, an image de-noising algorithm based on the wavelet combined with the Canny edge detection is proposed, which obtains a good result. The above algorithms are implemented based on OpenCV, which is more efficient, providing the conditions for subsequent image analysis and recognition. Experiments are carried out and the results show that the proposed algorithm is available and has a good performance.

A Study on Parallel and Pipelining Simulation Techniques for Edge Detection and Their Performance Analysis

2019 ◽  
Vol 16 (2) ◽  
pp. 568-572
Author(s):  
Merlin L. M. Livingston ◽  
Senthil C. Singh ◽  
K. Manojkumar ◽  
Sathish S. Kumar
Keyword(s):  
Edge Detection ◽  
Prime Number ◽  
Parallel Simulation ◽  
Canny Edge Detection ◽  
Simulation Techniques ◽  
Image Edge Detection ◽  
Multi Stage ◽  
Canny Edge ◽  
Image Edge ◽  
Sobel Edge Detection

Real processing components along with component simulators are combined together to construct a new virtual prototyping system. The increase in component simulators result in degraded performance of the simulation in distributed systems. The speed of simulation can be increased by doing parallel simulation techniques. Prime number test and Image edge detection are chosen to implement the parallel simulation techniques and achieved the expected results while implementing in real time applications. The prime number test calculates the number of processors in a system and the image edge detection can be done in two stages by Canny Edge detection and Sobel Edge detection. The Canny Edge detection is used to detect the edges in the images by using a multi-stage algorithm. The smaller, separable and integer valued filter in images are combined in horizontal and vertical directions by using the Sobel edge detection resulting in reduction of implementation cost. The tool named OpenMP is used for implementing the parallel simulation techniques by combining both the canny edge and Sobel edge detection. An add-on named MPI is used along with the OpenMP to reduce the implementation time in parallel processing.

Research of Image Edge Detection Algorithms Based on Android Platform

2014 ◽  
Vol 644-650 ◽  
pp. 1154-1157
Author(s):  
Yi He ◽  
Tian Li Li ◽  
Ying Qian Zhang
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Mobile Platform ◽  
Detection Algorithms ◽  
Image Edge Detection ◽  
Android Platform ◽  
Image Edge ◽  
Platform Development

With mobile platform development there are more and more Android-based image processing applications. The principles of four kinds of edge detection algorithms are analyzed in this paper and such algorithms are realized by adopting JNI technology based on android platform. At last the effect and efficiency of such algorithms are also compared and summarized.

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