Abstract
This paper proposes a fuzzy-based approach to edge detection in gray-level images. The proposed fuzzy edge detector involves two phases - global contrast intensification and local fuzzy edge detection. In the first phase, a modified Gaussian membership function is chosen to represent each pixel in the fuzzy plane. A global contrast intensification operator, containing three parameters, viz., intensification parameter t, fuzzifier fh and the crossover point xc, is used to enhance the image. The entropy function is optimized to obtain the parameters fh and xc using the gradient descent function before applying the local edge operator in the second phase. The local edge operator is a generalized Gaussian function containing two exponential parameters, & alpha; and & beta;. These parameters are obtained by the similar entropy optimization method. By using the proposed technique, a marked visible improvement in the important edges is observed on various test images over common edge detectors.
Original language | English |
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Title of host publication | International Conferen ON Information Technology 2004 |
Subtitle of host publication | Coding Computing |
Publisher | IEEE |
Pages | 665-670 |
Number of pages | 6 |
ISBN (Print) | 0769521088 |
DOIs | |
Publication status | Published - 24 Aug 2004 |
Event | 2004 International Conference on Information Technology: Coding Computing - Las Vegas, NV, United States Duration: 5 Apr 2004 → 7 Apr 2004 |
Conference
Conference | 2004 International Conference on Information Technology: Coding Computing |
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Abbreviated title | ITCC 2004 |
Country/Territory | United States |
City | Las Vegas, NV |
Period | 5/04/04 → 7/04/04 |
Keywords
- Contrast intensification operator
- Crossover point
- Edge detector
- Entropy
- Fuzzifier
- Fuzzy image processing
- Gaussian membership function
- Image enhancement
ASJC Scopus subject areas
- Software
- Information Systems
- Engineering(all)