基于TL-FCM的储粮害虫图像分割算法研究

摘要

An improved stored grain insect image segmentation of tower layered -fuzzy C -means algo-rithm(TL -FCM)was brought out to solve the problems such as high operation cost and high noise sensi-tivity in traditional fuzzy C -means algorithm (FCM).A tower layered structure was adopted to reduce computation time complexity,at the same time to restrict the target image subordinate degree of pixels. The constraint was added into the objective function of traditional algorithm,therefore neighborhood infor-mation was effectively constrained.Simulation results showed that the new algorithm needed less compu-tation time,effectively retained detail image information with ideal performance and results.%针对储粮害虫的图像识别需求，结合传统模糊 C 均值算法（FCM）在粮虫图像分割时运算开销过大、噪音敏感度偏高等不足，提出 TL －FCM（Tower layered FCM）粮虫图像分割改进算法。该方法采取塔状层次构架来降低运算的时间复杂度，同时对目标图像的像素隶属度进行约束，为传统算法中的目标函数引入约束项，从而有效约束邻域信息。仿真结果能够证明所构建的优化算法处理时间较短，且能够有效保留粮虫图像分割区域细节，算法性能和效果均比较理想。