Title :
An Adaptive Edge Detector Using Soft Mathematical Morphology
Author :
Xiaoxin Guo ; Zhiwen Xu ; Yinan Lu ; Yunjie Pang
Author_Institution :
Key Lab. of Symbol Comput. & Knowledge Eng., Jilin Univ., Changchun
Abstract :
In this paper, a novel adaptive soft morphological Laplacian (ASML) filter is proposed, based on a combination of the ideas of the soft morphological filtering and the Laplacian operator. ASML filter is an adaptive nonlinear edge detector. The adaptivity is achieved by employing four directional structuring elements and the dynamic repetition parameter. ASML filter has the capability of selecting the directional structuring element with the maximum response, whose direction varies depending on the change of directional edges. In addition, by replacing the Laplacian operator with soft morphological one, the ASML filter provides an alternative algorithm for edge detection and noise suppression. The experimental results show that the ASML filter outperforms the traditional edge detector in the two aspects
Keywords :
adaptive filters; edge detection; image denoising; mathematical morphology; ASML filter; Laplacian operator; adaptive edge detector; adaptive soft morphological Laplacian filter; noise suppression; soft mathematical morphology; Active contours; Computer vision; Data mining; Detectors; Humans; Image edge detection; Image segmentation; Level set; Morphology; Solid modeling;
Conference_Titel :
Computer and Information Technology, 2005. CIT 2005. The Fifth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
0-7695-2432-X
DOI :
10.1109/CIT.2005.60