摘要
智能图像导航技术已成为当今各领域的应用热点。针对于视觉系统对环境的强依赖性、传统Otsu算法只能用于灰度图的局限性、视觉系统精确模型建立困难的问题,设计了一种基于自适应阈值和改进粒子群融合的线性回归智能导航控制方法。所使用的自适应阈值截取算法,基于OPENMV视觉传感器能够提取图像彩色阈值中值信息的简单原理,设计能够在中值基础上左右循环加减,来实时截取目标阈值信息的创新算法。经实验效果对比验证,该算法能使OPENMV分别在彩图和灰度图模式下自动截取目标图像阈值,相较于传统阈值截取算法适用性更强。最后通过仿真结果证明基于以上组合算法的智能循迹控制能够有效降低视觉系统对环境的依赖性,方案可行。
Intelligent image navigation technology has become a prominent application in various fields.To address challenges such as environmental dependence,limitations of traditional algorithms,and difficulties in precise model establishment,a novel method combining adaptive thresholding and improved particle swarm fusion for linear regression intelligent navigation control is proposed in this paper.Experimental results validate the algorithm's effectiveness in real-time threshold extraction for target images,surpassing traditional methods.The combined algorithm significantly reduces the visual system's dependence on the environment,demonstrating the feasibility of the proposed approach.
出处
《工业控制计算机》
2024年第2期104-106,共3页
Industrial Control Computer
