快速傅立叶变换在苹果形状识别中的应用

Numerical integral method research based on Cloud Adaptive Particle Swarm Opti-mization algorithm

介绍了快速傅立叶变换在苹果形状识别中的应用,首先需要将苹果图像的边缘像素进行极坐标转换,经过FFT变换后的数据较多,因此还需采用主成份分析法对其进行处理,得到能够描述苹果形状的两个主成份值。

In order to improve robustness of the traditional adaptive particle swarm optimization algorithm, a novel adaptive algorithm which is called Cloud Adaptive Particle Swarm Optimization algorithm （CAPSO） is proposed. In the CAPSO, the inertia weight is adaptively varied depending on X-conditional cloud generator. CAPSO can improve its convergence capacity because of the stable tendency of cloud model. Meanwhile, it can remarkably avoid a local minimum using the randomness of cloud model to maintain diversity in the population. The performance of the CAPSO which is used for solving numerical integral of any function shows that the presented numerical integral al- gorithm has value in engineering practice.