An edge detection algorithm for online image analysis

Authors:
Azzam Sleit;Abdel Latif Abu Dalhoum;Ibraheem Al-Dhamari;Afaf Tareef
Affiliations:
Department of Computer Science, King Abdulla II School for Information Technology, University of Jordan, Amman, Jordan;Department of Computer Science, King Abdulla II School for Information Technology, University of Jordan, Amman, Jordan;Department of Computer Science, King Abdulla II School for Information Technology, University of Jordan, Amman, Jordan;Department of Computer Science, King Abdulla II School for Information Technology, University of Jordan, Amman, Jordan
Venue:
AMERICAN-MATH'10 Proceedings of the 2010 American conference on Applied mathematics
Year:
2010

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Abstract

Online image analysis is used in a wide variety of applications. Edge detection is a fundamental tool used to obtain features of objects as a prerequisite step to object segmentation. This paper presents a simple and relatively fast online edge detection algorithm based on second derivative. The proposed edge detector is less sensitive to noise and may be applied on color, gray and binary images without preprocessing requirements. The merits of the algorithm are demonstrated by comparison with Canny's and Sobel's edge detectors.