A novel approach for edge detection of images

Debashis Ganguly; Swarnendu Mukherjee; Kheyali Mitra; Partha Mukherjee

doi:10.1109/ICCAE.2009.39

A novel approach for edge detection of images

Debashis Ganguly, Swarnendu Mukherjee, Kheyali Mitra, Partha Mukherjee

Engineering Division (Great Valley)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Edge detection is a problem of fundamental importance in image analysis. Many approaches for edge detection have already revealed more are waiting to be. But edge detection using K-means algorithm is the most heuristic and unique approach. In this paper, we have proposed an algorithmic technique to detect the edge of any kind of true gray scale images considering the artificial features of the image as the feature set which is fed to K-Means algorithm for clustering the image and there to detect clearly the edges of the objects present in the considered image. The artificial features, which we have considered here, are mean, standard deviation, entropy and busyness of pixel intensity values.Keywords: Edge-detection, K-means algorithm, gray scale images, artificial feature, cluster, mean, standard deviation,entropy, busyness.

Original language	English (US)
Title of host publication	Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009
Pages	49-53
Number of pages	5
DOIs	https://doi.org/10.1109/ICCAE.2009.39
State	Published - Jun 8 2009
Event	2009 International Conference on Computer and Automation Engineering, ICCAE 2009 - Bangkok, Thailand Duration: Mar 8 2009 → Mar 10 2009

Publication series

Name	Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009

Conference

Conference	2009 International Conference on Computer and Automation Engineering, ICCAE 2009
Country/Territory	Thailand
City	Bangkok
Period	3/8/09 → 3/10/09

All Science Journal Classification (ASJC) codes

Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering

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10.1109/ICCAE.2009.39

Cite this

Ganguly, D., Mukherjee, S., Mitra, K., & Mukherjee, P. (2009). A novel approach for edge detection of images. In Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009 (pp. 49-53). Article 4804486 (Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009). https://doi.org/10.1109/ICCAE.2009.39

@inproceedings{4fe1518c3de74da38369e4eb0204b241,

title = "A novel approach for edge detection of images",

abstract = "Edge detection is a problem of fundamental importance in image analysis. Many approaches for edge detection have already revealed more are waiting to be. But edge detection using K-means algorithm is the most heuristic and unique approach. In this paper, we have proposed an algorithmic technique to detect the edge of any kind of true gray scale images considering the artificial features of the image as the feature set which is fed to K-Means algorithm for clustering the image and there to detect clearly the edges of the objects present in the considered image. The artificial features, which we have considered here, are mean, standard deviation, entropy and busyness of pixel intensity values.Keywords: Edge-detection, K-means algorithm, gray scale images, artificial feature, cluster, mean, standard deviation,entropy, busyness.",

author = "Debashis Ganguly and Swarnendu Mukherjee and Kheyali Mitra and Partha Mukherjee",

year = "2009",

month = jun,

day = "8",

doi = "10.1109/ICCAE.2009.39",

language = "English (US)",

isbn = "9780769535692",

series = "Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009",

pages = "49--53",

booktitle = "Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009",

note = "2009 International Conference on Computer and Automation Engineering, ICCAE 2009 ; Conference date: 08-03-2009 Through 10-03-2009",

}

Ganguly, D, Mukherjee, S, Mitra, K & Mukherjee, P 2009, A novel approach for edge detection of images. in Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009., 4804486, Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009, pp. 49-53, 2009 International Conference on Computer and Automation Engineering, ICCAE 2009, Bangkok, Thailand, 3/8/09. https://doi.org/10.1109/ICCAE.2009.39

A novel approach for edge detection of images. / Ganguly, Debashis; Mukherjee, Swarnendu; Mitra, Kheyali et al.
Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009. 2009. p. 49-53 4804486 (Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A novel approach for edge detection of images

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AU - Mukherjee, Swarnendu

AU - Mitra, Kheyali

AU - Mukherjee, Partha

PY - 2009/6/8

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N2 - Edge detection is a problem of fundamental importance in image analysis. Many approaches for edge detection have already revealed more are waiting to be. But edge detection using K-means algorithm is the most heuristic and unique approach. In this paper, we have proposed an algorithmic technique to detect the edge of any kind of true gray scale images considering the artificial features of the image as the feature set which is fed to K-Means algorithm for clustering the image and there to detect clearly the edges of the objects present in the considered image. The artificial features, which we have considered here, are mean, standard deviation, entropy and busyness of pixel intensity values.Keywords: Edge-detection, K-means algorithm, gray scale images, artificial feature, cluster, mean, standard deviation,entropy, busyness.

AB - Edge detection is a problem of fundamental importance in image analysis. Many approaches for edge detection have already revealed more are waiting to be. But edge detection using K-means algorithm is the most heuristic and unique approach. In this paper, we have proposed an algorithmic technique to detect the edge of any kind of true gray scale images considering the artificial features of the image as the feature set which is fed to K-Means algorithm for clustering the image and there to detect clearly the edges of the objects present in the considered image. The artificial features, which we have considered here, are mean, standard deviation, entropy and busyness of pixel intensity values.Keywords: Edge-detection, K-means algorithm, gray scale images, artificial feature, cluster, mean, standard deviation,entropy, busyness.

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BT - Proceedings - 2009 International Conference on Computer and Automation Engineering, ICCAE 2009

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A novel approach for edge detection of images

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