The two-dimensional minimum error(TME) thresholding method is a viable image segmentation method,but it has high complexity and is hardly used in real-time applications, and it is sensitive to noise, so an improved TME thresholding method was proposed. First the traditional 3×3 template was divided into two complementary parts: a cros-sing template and a 4-angle template,and the original image was median-filtered with two templates respectively to get two filtered images,then the efficient 2-D histogram was created and the better TME segmentation results were obtained using the two images,finally the formula of the TME was deduced and simplified to get the simplified formula, and a novel and fast algorithm was deduced with the TME computing features and the formula in order to reduce the computational complexity. Experimental results show that compared with the current TME thresholding algorithm, the proposed, method has not only better segmentation performance and robustness,but also its speed is much faster and its memory space is much less.%二维最小误差(TME)阈值法是一种有效的图像分割方法,但该方法计算复杂度高,难以实时处理,且该算法受噪声影响较大.针对此问题,提出了一种改进的TME阈值分割方法.首先,将传统的3×3模板分成互补的两个模板:十字模板和4-角域模板,并用这两个模板分别对原图像进行中值滤波得到两幅图像；然后,用两幅图像创建二维直方图并对其进行分割,以获得更好的分割性能；最后,对TME阈值选取公式进行简化得到最简公式,并利用此最简公式和其在二维直方图上的计算特性构建新型的快速算法,以便降低计算复杂度.仿真实验结果表明,与当前TME 阈值分割方法相比,所提方法不仅分割效果更好、稳定性更强,而且运行速度更快,占用的存储空间更少.
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