An edge detection algorithm using multi-state adalines
- Authors
- Paik, Joonki; BRAILEAN, JC; KATSAGGELOS, AK
- Issue Date
- Dec-1992
- Publisher
- Pergamon Press
- Keywords
- EDGE DETECTION; LINEAR NEURAL NETWORKS; PATTERN RECOGNITION
- Citation
- Pattern Recognition, v.25, no.12, pp 1495 - 1504
- Pages
- 10
- Journal Title
- Pattern Recognition
- Volume
- 25
- Number
- 12
- Start Page
- 1495
- End Page
- 1504
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/40263
- DOI
- 10.1016/0031-3203(92)90122-Y
- ISSN
- 0031-3203
1873-5142
- Abstract
- An edge detection algorithm using multi-state adaptive linear neurons (ADALINES) is presented. Although the tri-state ADALINE is only considered in this work, general multi-state input vectors with extreme values are shown to be linearly separable from the rest of the vectors with the same dimension. The input state of each ADALINE is defined using the local mean in a predefined mask in addition to the binary input states +/-1, the 0 input state is introduced for controlling the noise effect. If the input pattern matches one of the predefined edge patterns, the corresponding pixel is detected as an edge pixel. Experimental results are shown where the proposed detector is compared with both the Canny and LOG edge detectors.
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Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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