Affiliations: [a] School of Civil Engineering, Beijing Jiaotong University, Beijing, China
| [b] Department of Statistics, University of Wisconsin, Madison, WI, USA
Correspondence:
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Corresponding author. Qulin Tan, School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China. E-mail: qltan@bjtu.edu.cn.
Abstract: Through fuzzy membership function, the fuzzy algorithm of image boundary detection based on power function can transform ordinary space into generalized fuzzy space. However, the algorithm has a large amount of operation and slow speed, and it will lose the boundary information of some low gray value in the image, thus the quality of the image boundary detection is poor. Therefore, a bilinear fast enhancement fuzzy algorithm for image boundary detection is proposed in this paper. Based on the defined generalized fuzzy set GFS and the generalized fuzzy operator LGFO, the linear left half trapezoid fuzzy distribution function is first used as the generalized membership transformation of the image.The general space of grayscale image is transformed into generalized fuzzy space, and then boundary detection algorithm based on bilinear fast image enhancement is used to transform color image into gray scale and transform to generalized fuzzy set. The generalized fuzzy operator LGFO is used to enhance the contrast of the generalized fuzzy sets. The generalized fuzzy set after the enhancement is transformed into an ordinary fuzzy subset. The boundary extraction is carried out for the ordinary fuzzy subset after processing, and the image boundary detection is realized. The experimental results show that the proposed algorithm greatly improves the speed and quality of image boundary detection.
Keywords: Image boundary detection, bilinear, fast fuzzy enhancement, LGFO, generalized fuzzy space
