基于GSPN的飞机测试性指标确定方法研究

针对现有的图像分割中自适应分割方法的研究难点,以及传统的模糊阈值分割法中存在窗宽不能自动获取的问题,在确定隶属函数的前提下,以图像的直方图为依据,利用分段计算和反变换的方法,提出了一种自适应模糊阈值的图像分割方法,并将该方法应用于机场目标的分割。该方法实现其窗口宽度的自适应选取,并且有效改善了模糊阈值法对直方图呈不明显双峰的图像分割困难的缺点,拓展了模糊阈值图像分割方法的适用范围,改善了模糊阈值分割方法的分割效果。实验结果表明,该方法对直方图呈单峰和多峰分布的的图像有较好的分割效果和效率。

Research on Determination Method for Testability Index of Aircraft Based on GSPN

The existing adaptive segmentation methods still exist difficulties, and traditional fuzzy threshold segmentation methods can not automatically obtain the window width, under the premise of determining membership functions. According to image histogram, an adaptive fuzzy threshold image segmentation method is proposed to extract target features for airports by using the burst method of calculation and the inverse transform. The method realizes the adaptive selection of window width, and overcomes the disadvantage of fuzzy threshold methods for image histogram difficulty without obvious bimodal effectively, expands the application scope of fuzzy threshold image segmentation methods, which improves segmentation results of the fuzzy threshold segmentation methods. Experimental results show better segmentation results and efficiency can be achieved by the proposed method with single peak and multi-peak distribution histogram.