Real time sobel square edge detector for night vision analysis

Wang, Ching Wei (2006) Real time sobel square edge detector for night vision analysis. In: Image analysis and recognition. Lecture notes in computer science (4141). Springer, Berlin, pp. 404-413. ISBN 9783540448914

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Abstract

Vision analysis with low or no illumination is gaining more and more attention recently, especially in the fields of security surveillance and medical diagnosis. In this paper, a real time sobel square edge detector is developed as a vision enhancer in order to render clear shapes of object in targeting scenes, allowing further analysis such as object or human detection, object or human tracking, human behavior recognition, and identification on abnormal scenes or activities. The method is optimized for real time applications and compared with existing edge detectors. Program codes are illustrated in the content and the results show that the proposed algorithm is promising to generate clear vision data with low noise.

Item Type: Book Section
Additional Information: Vision analysis with low or no illumination is gaining more and more attention recently, especially in the fields of security surveillance and medical diagnosis. In this paper, a real time sobel square edge detector is developed as a vision enhancer in order to render clear shapes of object in targeting scenes, allowing further analysis such as object or human detection, object or human tracking, human behavior recognition, and identification on abnormal scenes or activities. The method is optimized for real time applications and compared with existing edge detectors. Program codes are illustrated in the content and the results show that the proposed algorithm is promising to generate clear vision data with low noise.
Keywords: vision analysis
Subjects: G Mathematical and Computer Sciences > G400 Computer Science
Divisions: College of Sciences > Faculty of Science > Lincoln School of Computer Science
Depositing User: Bev Jones
Date Deposited: 26 Sep 2006
Last Modified: 13 Mar 2013 08:22
URI: http://eprints.lincoln.ac.uk/id/eprint/107

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