Dual-channel output contour detection method based on encoding and decoding structures

Abstract

The invention provides a dual-channel output contour detection method based on encoding and decoding structures. In the encoding stage, image feature information is extracted through an improved VGG16network, in the decoding stage, feature information of different scales is fused from bottom to top, and the same label is used for carrying out deep supervision on output contour images of two channels. According to the method, the feature maps of different scales are fused in a bottom-up layer-by-layer decoding mode, so that the extracted image feature information is richer; adding a channel attention structure in a feature fusion stage, and performing feature map sampling by using sub-pixel convolution; a proper loss function is designed to solve the problem of imbalance of training samples; and a data set is amplified by using a data enhancement method, so that the generalization ability of the model is improved. According to the method, the target contours of the BSDS500 public dataset and the customized woodcarving contour detection data set can be effectively extracted, and the detection contour lines are fine.

Description

technical field [0001] The invention belongs to the field of image processing and computer vision, and relates to a dual-channel output contour detection method based on an encoding and decoding structure, which is essentially a problem of binary classification of image pixels by using a convolutional neural network. Background technique [0002] Contour detection is the core task in the field of computer vision. Extracting the target contour in the image through the rich feature information of the digital image is the basis of advanced visual tasks such as target detection, semantic segmentation, and defect recognition. Accurately extracting image target contours is still a challenging task due to factors such as lighting, camera equipment precision, and target contour complexity. [0003] The traditional edge detection operator method is to detect the contour by looking for pixels with obvious brightness changes in the digital image. The contour detection method based on ...

AI Technical Summary

Problems solved by technology

At this stage, the contour detection algorithm based on convolutional neural network mainly has difficulties such as rough contour line detection, inaccurate positioning, and unbalanced training samples.

Images