基于蛇优化算法的Otsu图像分割方法

Otsu算法是图像处理中运用广泛的图像分割方法，尽管有着计算简单、准确的特性，但因为需要进行穷举运算，所以计算效率不高。为提高图像分割的实时性，引入了蛇优化算法(SO)对Otsu进行了优化，创建了基于蛇优化算法的Otsu图像分割方法(SO-Otsu)。在该算法中，利用蛇优化算法来模拟蛇的特性进行最佳阈值的寻找，以降低迭代时间，提升计算速度。在仿真实验中，利用经典的Lena、Peppers、Goldhill、Cameraman图片进行测试，与基于果蝇优化算法的Otsu方法(FOA-Otsu)和基于麻雀搜索算法的Otsu方法(SSA-Otsu)进行对比。并通过计算峰值信噪比(PSNR)、结构相似性(SSIM)、特征相似性(FSIM)和计算时间作为评价指标结果进行评估。结果表明，与其他算法相比，算法计算效率高、分割细节效果好且综合分割性能优异，为提高图像分割的计算效率提供了一种理想的工具。

Structural Design of High-precision Positioning System in Weak Signal Environment Based on UWB and IMU Fusion

Aiming at the problem that indoor positioning technology based on wireless ultra-wideband pulse technology is susceptible to non-line-of-sight effects and multipath effects in confined spaces and weak signal environments, a high-precision positioning system based on UWB and IMU in a confined environment is designed. The STM32 chip is used as the main control, and the data information of IMU and UWB is fused by the fusion filtering algorithm. Finally, the real-time information of the positioning is transmitted to the host computer and the cloud. The experimental results show that the positioning accuracy and positioning stability of the system have been improved in the non-line-of-sight case of closed environment. The system has high positioning accuracy in a closed environment, and the components used are consumer-grade, which has strong practicability.