VISION-BASED WORKING AREA BOUNDARY DETECTION SYSTEM AND METHOD, AND MACHINE EQUIPMENT

摘要

Provided are a vision-based working area boundary detection system and method, and a machine equipment. The method, in implementation, comprises: firstly, a constructed neural network model performing autonomous training and learning based on a training data set, and extracting and learning corresponding working area features; and then the neural network model completing training and learning, and performing real-time image semantic segmentation on the acquired video image based on the working area features extracted by the training and learning, thereby perceiving an environment and identifying a boundary of a working area. The method is based on a neural network machine vision technology, the boundary of the working area can be efficiently recognized by extracting and learning the working area features in the earlier stage, and the robustness to a change in environments such as illumination is relatively high.