Abstract
In this paper, we proposed an adaptive enhancement algorithm based on fuzzy relaxation. Firstly, the OTSU algorithm is used to classify background and objective, and the crossover points for each pixel are defined by the classification results. Then, the concept of fuzzy contrast based on the image normalization is introduced, and the value of fuzzy contrast is defined as a image contrast feature plane. Secondly, at basis of the fuzzy characteristic of the hyperbolic tangent, a novel membership function is proposed, the crossover points and the adaptive function curve can achieve the best by adjusting the control parameters. Finally, the fuzzy contrast feature plane is mapped to gray level plane using the method of linear transformation. The experiment obtains excellent results which is only one time iteration. The linear transformation reduces the lose of the adjacent materials bag image’s edge information and improves the operational efficiency. The analysis experimentally demonstrates that proposed algorithm is adaptive and the image details also have been preserved.
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Jia, W., Wang, Y., Liu, Y., Fan, L., Ruan, Q. (2014). An Adaptive Enhancement Algorithm of Materials Bag Image of Industrial Scene. In: Zhang, X., Liu, H., Chen, Z., Wang, N. (eds) Intelligent Robotics and Applications. ICIRA 2014. Lecture Notes in Computer Science(), vol 8918. Springer, Cham. https://doi.org/10.1007/978-3-319-13963-0_23
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DOI: https://doi.org/10.1007/978-3-319-13963-0_23
Publisher Name: Springer, Cham
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