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