In this work, a highly customizable and scalable vision based system for automation of mechanical assembly lines is described. The proposed system calculates the features that are required to classify and identify the different kinds of bolts that are used in the assembly line. The system describes a novel method of calculating the pitch of the bolt in addition to bolt identification and calculating the dimensions of the bolts. This identification and classification system is extremely lightweight and can be run on bare minimum hardware. The system is very fast in the order of milliseconds, hence the system can be used successfully even if the components are steadily moving on a conveyor. The results show that our system can correctly identify the parts in our dataset with 98% accuracy using the calculated features.

翻译：本文描述了一种高度可定制且可扩展的基于视觉的自动化机械装配线系统。所提出的系统计算所需特征，以分类和识别装配线上使用的不同类型螺栓。该系统除螺栓识别和尺寸计算外，还描述了一种新颖的螺栓螺距计算方法。该识别与分类系统极为轻量，可在最低硬件配置下运行。系统速度快至毫秒量级，因此即便部件在传送带上稳定移动，也能成功应用。结果表明，利用计算所得特征，我们的系统能够以98%的准确率正确识别数据集中的部件。