A design approach of ten practical guidelines establishes a strong architectural method for satisfying application requirements for machine vision and imaging system developers. Because each application is often unique, vision applications are difficult to develop. As a general rule, machine vision companies use these design steps to create a custom machine-vision application.
Control inspection goals
The initial step to install an automated machine-vision system happens to be to regulate the cost budget and the application assistances. Evidently, the vision system’s cost have to be recouped in the short term by improving the manufacturing process and product yield or lowering overhead costs such as support, returns, and so on.
Estimation of the inspection time
A different technology should be considered if the product inspection time is ten times longer than the overall system inspection time. The inspection necessities in some applications use to be such that the machine-vision system cannot be used to reduce speed the production procedure. Material handling, image achievement, and data treating should all be measured when calculating the general system inspection time.
The following are some techniques that can help you improve your inspection time performance:
– Digital cameras— provide higher frame rates (up to thousands per second) than analogue cameras (30 frames per second).
– MMX-enabled vision software— can increase system processing by as much as 400% for some functions
– Image-acquisition hardware— On-board partial image scanning, programmable region of interest, and on-board pixel decimation are among the image-processing techniques that can be supported. The goal of this design strategy is to reduce the number of processing pixels in order to reduce the amount of time it takes to process an image.
Use the most recent personal computer available, as PC processors continue to improve.
Classify structures or defects
To help evaluate all of the defects, statistical techniques such as ranking the defects from highest to lowest probability can be used. If the defects cannot be classified, it will be difficult to automate the inspection process. It is often preferable to enlist the help of a systems integrator or a vision vendor at this stage. Many vision vendors, on the other hand, will evaluate an application solution primarily using their own hardware and software.
Select lighting and material-handling method
The use of lighting and part-handling devices ensures that the image is captured consistently, resulting in easier software processing. Conveyors, x-y positioning stages, robotic arms, motors, and motion-control hardware and software are all available from material-handling companies. Many vendors are willing to work with you to specify a vision system. Overall, the cost of the vision system is determined by the part manufacturing process, accuracy, and production speed.
Select the optics
When choosing a lens and a camera, the minimum resolution and field-of-view (FOV) requirements are two important factors to consider. Consider the need to inspect a videotape for small surface defects when using these parameters in a practical application. Within a vertical FOV of 20 mm, which is the viewing area of the camera and lens system, the minimum resolution requirements are to find defects as small as 0.25 mm. Four pixels per 0.25 mm minimum defect size would ensure that the defect is detected in this application. To achieve this minimum resolution within the FOV using a four-pixel/0.25-mm resolution, 16 pixels/mm over a 20-mm FOV is required. These specifications dictate that a camera with a sensor array of at least 320 pixels should be used.
Select the image-acquisition hardware
Whether the vision system will be used in-line with a manufacturing process or as an off-line inspection system, determines which camera to use and how much image acquisition rate is required. The frame rate of analogue monochrome cameras determines the image-acquisition card’s minimum acquisition rate and processing time.