Proceedings. ITCC 2005 International Conference on Information Technology: Coding and Computing (2005)
Las Vegas, NV, USA
April 4, 2005 to April 6, 2005
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ITCC.2005.158
John See , Multimedia University, Cyberjaya, Malaysia
Madasu Hanmandlu , I.I.T. Delhi, India
Shantaram Vasikarla , InterContinental University, Los Angeles, CA
Many edge detection schemes suffer from the lack of image quality at the global level. Global properties are more vital in grayscale images due to loss of hue and texture. This paper proposes a novel fuzzy-based Gaussian edge detector that uses both global and local image properties for grayscale images. In the global contrast intensification phase, each pixel in an image is represented in the fuzzy domain using a modified Gaussian membership function. A nonlinear contrast intensification function containing three parameters is used to further enhance the image. In the local phase, we present a novel fuzzy parameterized Gaussian-type edge detector mask containing two fuzzifier parameters, which are chosen based on experimental selection rules. Optionally, the fuzzy image entropy function can be used to optimize all the parameters through simple gradient descent technique. In experiments conducted on various classic images, this algorithm showed notable visual improvement on both strong and weak edges in comparison with common edge detectors.
Image enhancement, Gaussian edge detector, Gaussian membership function, contrast intensification, entropy optimization
J. See, S. Vasikarla and M. Hanmandlu, "Fuzzy-based Parameterized Gaussian Edge Detector Using Global and Local Properties," Information Technology: Coding and Computing, International Conference on(ITCC), Las Vegas, Nevada, 2005, pp. 101-106.