基于注意力机制和图像轮廓的实例分割算法OA

Based on image contour,the instance segmentation method uses fewer contour nodes to represent an object,which effectively reduces the number of algorithmic parameters and improves its operation efficiency.Howev-er,with the segmentation result of poor quality,it is no match for traditional pixel-by-pixel processing segmenta-tion algorithm in terms of accuracy.To improve the accuracy of the algorithm,it is of great necessity to introduce a refined model of the instance segmentation(Attend the Contour snake,AC-snake),which is based on image con-tour with a combination of attention mechanism.An improved Largekernel + is added to the backbone network to im-prove the receptive field of the model and extract richer feature information.The network structure at the contour ver-tex deformation stage is improved,and the Dual Channel attention(DC-attentio)module is combined to enhance the effective information of contour vertex,reduce the invalid parameters in the training network,and improve the de-tection accuracy and training speed.The experimental results show that in Cityscapes validation data set,the im-proved model proposed in this study has improved performance when compared with the original model.