机器视觉2D技术发展至今已经有30多年了，技术相对成熟， 尺寸检测设备，在产品质量控制自动化领域广泛使用，但已经很难满足现今的技术需求了。

如今市场上产品品质对于精度要求越来越高，机器视觉3D技术相对于2D会更受生产企业的欢迎，3D视觉可以测量产生2D系统不能的形状信息。 因此，可以测量与形状相关的特征，例如物体平直度， 缺陷检测设备，表面角度和体积。

Machine vision 2D technology has been developed for more than 30 years. It is relatively mature and widely used in the field of product quality control automation, but it is difficult to meet the current technical needs.

Nowadays, product quality in the market requires higher and higher precision. Compared with 2D, machine vision 3D technology will be more popular with manufacturers. 3D vision can measure the shape information that can not be generated by 2D system. Therefore, shape-related features such as flatness, surface angle and volume can be measured.

 

3D传感器中的所有组件都被牢固地安装在单个光机械组件上，外观检测设备，以确保重复性，焦距相对于发射器和成像器平面锁定在位，并且包括温度补偿功能，以便纠正由于金属蠕变而引起的移动。

3D机器视觉的另一个好处是， 例如，可以用多个扫描仪扫描诸如卡车框架的大物体。

随着人工智能的更多应用落地，深度学习成为机器视觉检测的热门发展趋势，深度学习是机器学习的一个领域，它使计算机能够通过卷积神经网络等体系结构进行训练和学习。它通过处理数据和创建用于决策的模式来模仿人类大脑的工作方式。

未来几年深度学习技术将会继续发挥重要作用。

All components of the 3D sensor are firmly mounted on a single optical-mechanical component to ensure repeatability, focal length is locked in place relative to the plane of the transmitter and the imager, and temperature compensation is included to correct the movement caused by metal creep.

Another advantage of 3D machine vision is that, for example, large objects such as truck frames can be scanned with multiple scanners.

With more applications of artificial intelligence coming to the ground, in-depth learning has become a popular trend in machine vision detection. In-depth learning is an area of machine learning, which enables computers to train and learn through convolutional neural networks and other architectures. It mimics the way the human brain works by processing data and creating patterns for decision-making.

In the next few years, in-depth learning technology will continue to play an important role.

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