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Edge Detection using Skewed and Elongated Basis Functions

S. Anand, S.Jeeva, T.Thivya Published in Image Processing

International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
10.5120/ijais12-450163
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  1. S Anand, S.Jeeva and T.Thivya. Article: Edge Detection using Skewed and Elongated Basis Functions. International Journal of Applied Information Systems 1(4):28-34, February 2012. BibTeX

    @article{key:article,
    	author = "S. Anand and S.Jeeva and T.Thivya",
    	title = "Article: Edge Detection using Skewed and Elongated Basis Functions",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 1,
    	number = 4,
    	pages = "28-34",
    	month = "February",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

This paper proposed an edge detection using Skewed and Elongated Basis functions (SEBF). In an image, edges present at any directions and any scale. Common edge detection algorithms are single scale, and limited in directions. The proposed method efficiently removes these difficulties by using SEBF that are having multiscale and non separable properties. The two dimensional non separable properties of SEBF provide multiple directions, whereas the multiscale to explore the hidden edge information at various scales. The SEBF are derived from anisotropic directionlets are applied for edge detection to effectively preserving edges in all orientations and scales. This paper uses Figure of Merit (F), accuracy, sensitivity, specificity characteristics to analyze the performances. The experimental results showed that the proposed algorithms provide improvement in all performance measure.

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Keywords

Edge Detection, Directionlet Basis, Scale Multiplication