Design of Intelligent Classification Algorithm for Mechanical Part Image Based on Fusion Fluctuation Suppression
To improve the image classification performance,a mechanical part image classification algorithm based on binocular weighted model fusion and fluctuation suppression is proposed.Wavelet decomposition on the image is performed to obtain high-frequency components,and the processed components are reconstructed to obtain a denoised image.The denoised image is decomposed into a Laplacian pyramid sequence,and by fusing the image through average gradient and regional energy fusion coefficient,a binocular weighted model is introduced to complete image reconstruction and suppress fusion coefficient fluctuations.With adoption of CNN to extract image features and filters to train features,ensemble learning strategies are introduced to gain classification labels,achieving image classification.The experimental results show that the proposed algorithm has small fluctuations in fusion coefficients and good image classification performance.
万方数据
维普
