An improved edge detection algorithm based on area morphology and maximum entropy

Li Shuyu; Pu Fang; Li Deyu

doi:10.1109/ICICIC.2007.148

An improved edge detection algorithm based on area morphology and maximum entropy

Li Shuyu^*
, Pu Fang
, Li Deyu

^*Corresponding author for this work

School of Biological Science and Medical Engineering

Beihang University

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

5 Scopus citations

Abstract

A novel method based on area morphology and maximum entropy theory for edge detection is presented. Area morphological filters can enable the elimination of connected components within image level sets by selecting different area scales. Using area morphology approach, thin, closed contours without boundary distortion can be provided, which are suitable for use in image segmentation. By the introduction of maximum entropy, the improved method not only preserves the advantages of the area morphology, but also can automatically highlight desired objects against background without user input or parameter specification. The experimental results show the improved method can obtain good results by selecting optimal image scales automatically.

Original language	English
Title of host publication	Second International Conference on Innovative Computing, Information and Control, ICICIC 2007
DOIs	https://doi.org/10.1109/ICICIC.2007.148
State	Published - 2008
Event	2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007 - Kumamoto, Japan Duration: 5 Sep 2007 → 7 Sep 2007

Publication series

Name	Second International Conference on Innovative Computing, Information and Control, ICICIC 2007

Conference

Conference	2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007
Country/Territory	Japan
City	Kumamoto
Period	5/09/07 → 7/09/07

Access to Document

10.1109/ICICIC.2007.148

Cite this

Shuyu, L., Fang, P., & Deyu, L. (2008). An improved edge detection algorithm based on area morphology and maximum entropy. In Second International Conference on Innovative Computing, Information and Control, ICICIC 2007 Article 4428178 (Second International Conference on Innovative Computing, Information and Control, ICICIC 2007). https://doi.org/10.1109/ICICIC.2007.148

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title = "An improved edge detection algorithm based on area morphology and maximum entropy",

abstract = "A novel method based on area morphology and maximum entropy theory for edge detection is presented. Area morphological filters can enable the elimination of connected components within image level sets by selecting different area scales. Using area morphology approach, thin, closed contours without boundary distortion can be provided, which are suitable for use in image segmentation. By the introduction of maximum entropy, the improved method not only preserves the advantages of the area morphology, but also can automatically highlight desired objects against background without user input or parameter specification. The experimental results show the improved method can obtain good results by selecting optimal image scales automatically.",

author = "Li Shuyu and Pu Fang and Li Deyu",

year = "2008",

doi = "10.1109/ICICIC.2007.148",

language = "英语",

isbn = "0769528821",

series = "Second International Conference on Innovative Computing, Information and Control, ICICIC 2007",

booktitle = "Second International Conference on Innovative Computing, Information and Control, ICICIC 2007",

note = "2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007 ; Conference date: 05-09-2007 Through 07-09-2007",

}

Shuyu, L, Fang, P & Deyu, L 2008, An improved edge detection algorithm based on area morphology and maximum entropy. in Second International Conference on Innovative Computing, Information and Control, ICICIC 2007., 4428178, Second International Conference on Innovative Computing, Information and Control, ICICIC 2007, 2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007, Kumamoto, Japan, 5/09/07. https://doi.org/10.1109/ICICIC.2007.148

An improved edge detection algorithm based on area morphology and maximum entropy. / Shuyu, Li; Fang, Pu; Deyu, Li.
Second International Conference on Innovative Computing, Information and Control, ICICIC 2007. 2008. 4428178 (Second International Conference on Innovative Computing, Information and Control, ICICIC 2007).

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

TY - GEN

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AU - Shuyu, Li

AU - Fang, Pu

AU - Deyu, Li

PY - 2008

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N2 - A novel method based on area morphology and maximum entropy theory for edge detection is presented. Area morphological filters can enable the elimination of connected components within image level sets by selecting different area scales. Using area morphology approach, thin, closed contours without boundary distortion can be provided, which are suitable for use in image segmentation. By the introduction of maximum entropy, the improved method not only preserves the advantages of the area morphology, but also can automatically highlight desired objects against background without user input or parameter specification. The experimental results show the improved method can obtain good results by selecting optimal image scales automatically.

AB - A novel method based on area morphology and maximum entropy theory for edge detection is presented. Area morphological filters can enable the elimination of connected components within image level sets by selecting different area scales. Using area morphology approach, thin, closed contours without boundary distortion can be provided, which are suitable for use in image segmentation. By the introduction of maximum entropy, the improved method not only preserves the advantages of the area morphology, but also can automatically highlight desired objects against background without user input or parameter specification. The experimental results show the improved method can obtain good results by selecting optimal image scales automatically.

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DO - 10.1109/ICICIC.2007.148

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SN - 9780769528823

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BT - Second International Conference on Innovative Computing, Information and Control, ICICIC 2007

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Y2 - 5 September 2007 through 7 September 2007

ER -

An improved edge detection algorithm based on area morphology and maximum entropy

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