標題: | Fuzzy-logic-based modified single-layer perceptron segmentation network |
作者: | Chang, JY Chen, JL 電控工程研究所 Institute of Electrical and Control Engineering |
公開日期: | 1998 |
摘要: | In this paper, we propose a modified singlelayer perceptron (MSLP) segmentation network for object extraction. We select a sigmoid gray level transfer function from the histogram of the input image and map the input gray levels into the interval [0, 1]. Then we adopt the linear index of fuzziness of the output nodes as the error function of the image segmentation system to incorporate the learning capability of a neural network. Our scheme can successfully extract multiple objects with different gray levels. To further enhance the capability of the segmentation system, the proposed network is incorporated with fuzzy if-then rules to adaptively adjust the threshold of the activation function of the output neuron for best matching the local characteristics of the image. Fuzzy if-then rules involving the edge intensities and vertical positions of pixels are reasoned to determine the threshold adaptively. From the result of segmenting the forward looking infrared (FLIR) image, a better segmentation image has been obtained by incorporating fuzzy if-then rules with the MSLP segmentation technique. |
URI: | http://hdl.handle.net/11536/19491 |
ISBN: | 0-7803-4778-1 |
ISSN: | 1062-922X |
期刊: | 1998 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5 |
起始頁: | 3283 |
結束頁: | 3288 |
顯示於類別: | 會議論文 |