DocumentCode
2795731
Title
Progressive Edge Detection on multi-bit images using polynomial-based binarization
Author
Govindarajan, Barghavi ; Panett, K. ; Agaian, Sos
Author_Institution
Dept. of Electr. & Comput. Eng., Tufts Univ., Medford, MA
Volume
7
fYear
2008
fDate
12-15 July 2008
Firstpage
3714
Lastpage
3719
Abstract
Edge detection is an important image processing operation with applications such as 3D reconstruction, recognition, image enhancement, image restoration and compression. Several edge detectors have been developed in the past decades although no single edge detector is best suited for all applications [S]. This paper presents a new concept in edge detection that is better suited for application-specific image processing. The grayscale or multi-bit image is mapped to a set of several binary images. This is followed by the application of edge detection algorithms on these binary images and a fusion of the individual edge maps. A novel polynomial based binarization method is also presented. An evolutionary approach to the fusion of edgemaps renders the algorithm adaptive. Experimental results have shown that this new concept has several advantages. It produces edges of better quality; it can be used in a dasiaprogressivepsila manner to save on computations and increase usability. Further, it can be used to take advantage of multiple popular edge detection algorithms (Danahy et al., 2007; Danahy et al., 2006; Danahy, 2006).
Keywords
edge detection; evolutionary computation; image enhancement; image reconstruction; 3D reconstruction; evolutionary approach; image compression; image enhancement; image processing operation; image restoration; multi-bit images; polynomial-based binarization; progressive edge detection; Detectors; Gray-scale; Image coding; Image edge detection; Image enhancement; Image processing; Image recognition; Image reconstruction; Image restoration; Polynomials; Edge Detector; binarization; image quality; progressive edge detection; threshold;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Electronic_ISBN
978-1-4244-2096-4
Type
conf
DOI
10.1109/ICMLC.2008.4621051
Filename
4621051
Link To Document