基于改进Sobel算子的语义分割算法

Semantic Segmentation Algorithm Based on Improved Sobel Operator

针对常用语义分割算法存在丢失边缘信息导致分割不够精确的问题,通过结合边缘检测算法进行语义分割,有效地改善了分割不准确及边缘模糊的问题。算法采用并行结构,通过边缘检测子网络所提取的边缘特征来对语义分割子网络所提取的语义分割特征进行信息的补充,采用concat融合两路特征进行卷积操作来获取最终分割结果。实验基于TensorFlow平台进行,所提出方法相比以往算法在计算速度接近的同时真实值和预测值的交并比上取得了一定提升,增强了分割结果。

Aiming at the problem of inaccurate segmentation caused by the loss of edge information in common semantic segmentation algorithms,the problem of inaccurate segmentation and fuzzy edge is effectively improved by semantic segmentation combined with edge detection algorithm.The algorithm adopts parallel structure.The edge features extracted by the edge detection subnetwork are used to supplement the semantic segmentation features extracted by the semantic segmentation sub-network.The final segmentation result is obtained by convolution operation of concat fusion of two features.The experiment is based on TensorFlow platform.Compared with the previous algorithm,the proposed method achieves a certain improvement in the intersection and union ratio of the real value and the predicted value,and enhances the segmentation results.