Increase Accuracy of Optical 3D Measurements

Posted by Gretchen Alper on Wed, Jul 9, 2014

In semiconductor and electronics manufacturing, there has been a move towards 3D measurements to provide accurate process control of smaller dimensions for higher yield and quality of new packaging technologies.  For example in electronics manufacturing a 2D view from the top only allows for detection of defects such as shifts, rotations, and cracks, but not whether components are flat on the board or the volume of solder paste.

There are several 3D optical measurement techniques including stereoscopy, triangulation, interferometry, con-focal vertical scanning, and time of flight.  As with 2D measurements, the camera must obtain the right details in the input image in order to get accurate measurements.  Camera specifications that drive the ability to get the correct starting image include signal-noise-ration (SNR), dynamic range, uniformity, linearity, and stability.  These become increasingly important with more precise techniques.

3d camera requirements machine vision


This figure shows how the performance of the camera must increase in different 3D measurement techniques. 


With all of the necessary starting information per image, the other consideration is that some 3D measurement systems may use 4-5 images per inspected ROI.  More advanced systems use 20 images or even more to increase measurement accuracy and to add color vision.  Many 2D measurements only required 1 image so this change results in more demands on the camera-based imaging system to get the necessary information without impacting throughput

One of the ways to get multiple images without slowing down the system is by using a higher resolution camera.  Higher resolution cameras allow for a larger area to be inspected at once and provide more data, especially for smaller details.  BUT the camera frame rate must also be high (for example 4 or 12 Megapixel at 180 fps or even 25 Megapixel at 32 fps and higher) with the necessary image quality over the full resolution and also maintained at the high frame rates. 

Since multiple images are combined, the stability and reproducibility in the camera is more critical than in the past.  Only intentional changes can occur between the images. This means black level, gain, among others must be exactly the same for all of the images.  These parameters are all controlled through careful design and implementation by the camera manufacturer.

Another option to efficiently capture multiple images is through multiple cameras.  This could mean fewer illuminators and less stringent requirement on the speeds of the camera.  This is attractive as it allows for scalability using more low cost cameras for higher end systems.  This should be done with caution though as the cameras can have lower frame speed, but need to be extremely consistent, and well-matched for this technique to be effective.

Regardless of the specific implementation, 3D measurements mean increasing demands on the performance and reliability of the machine vision camera for the accuracy needed in semiconductor and electronics metrology.  Depending on the specific measurement method, the higher the demands where the image sensor selection and then full optimization in the camera become more imperative.


Related Posts:

Machine Vision Camera Requirements for 3D AOI

3D Measurements and Inspection Advancing Machine Vision Cameras

High-resolution cameras combined with high speeds support latest smartphones production demand


Topics: Applications, Vision System Optimization