Machine Vision Software is Making Great Strides in Imaging Capabilities

The capabilities of a given machine vision or embedded vision system rely on more than just the hardware of the camera. The central hardware components of a camera are often viewed as solely responsible for the system’s performance – components such as the sensor, the lens, the interface and more are given all the credit, but software can be just as impactful.

Recently, the software used in machine vision and embedded vision systems has been making major advances. From the food and beverage industry to the electronics industry, improving machine vision software is having an impact.

4 Types of Machine Vision Software Advances

While advances have happened across the board, there are four areas in which major gains have been made.

1. High Dynamic Range Inspection

The electronics industry is running their lines faster and with higher resolution, introducing higher signal-to-noise ratios (SNR). Machine vision software that enhances the dynamic range of cameras is being used to reduce SNRs for more accurate inspections. This software can be highly customized based on the needs of a particular manufacturer.

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2. Optical Character Recognition Software

Optical character recognition (OCR) has historically been limited to black text on white backgrounds, but this is rarely the case in real-world manufacturing. New OCR software can detect characters on busy backgrounds, and some of the newest software can even recognize characters when new fonts are introduced.

3. 3-Dimensional (3D) Imaging

A number of manufacturers have been developing photometric 3D algorithms to read 3D text, among other things. Some forms of 3D vision software combine multiple images of the same part to enhance contrast in 3D images for more accurate imaging results.

4. Deep Learning

Deep learning is one of the latest buzzwords in machine vision, but some companies are making strides in this technology. A few of the largest software developers have image classification tools based on deep learning that detect hard-to-define defects and product variations.

Machine vision software plays a critical role in the performance of a vision system. The four types of software mentioned above are among the most rapidly advancing, but gains have been made across the board.

More than ever, identifying the right machine vision software for your application is just as important as finding the right machine vision hardware.