高精度自适应阈值分割算子的设计

Design of thresholding segmentation operator with high precision self-adaptive capacity

针对复杂背景下的目标区域识别精度不高、自适应能力不足等问题,对纹理图像的特点和空间域形成规则进行了研究,提出了一种适合在非规则纹理图像中寻找目标区域的阈值分割新方法。实验表明,该方法具有良好的自适应能力。特别是在有较高能量分布的随机纹理图像中,该方法分割精度较高。

Focusing on the problems about low precision and self-adaptive capacity in the identification of target area under complicated background, a new thresholding segmentation algorithm with self-adaptive capacity and high precision was introduced in the test after the investigation of texture image and the space area form rule. Results demonstrate that the algorithm has fine self-adaptive capacity. Particularly in random texture images with higher energy distribution, a high precision could be obtained with this algorithm.