You recently released the LSS-2404 lighting controller for computational imaging. What led to this product being developed, and why?

Precision illumination is always critical to high-performance machine vision systems. CCS recognized the fact that by combining illumination with computation, one can take imaging technology to the next level.

The LSS-2404 programmable lighting controller was developed primarily to serve as the "heart" of any computational imaging system. Image acquisition has not changed appreciably since the beginning of the machine vision industry roughly 40 years ago. Cameras take a single exposure, using fixed optics and lighting conditions.

When system builders are faced with tough imaging challenges, this model doesn’t work very well. Typical solutions are to try different lighting and/or lensing or to "fix" the problem of poor image quality in software. Both approaches add extra time and cost to imaging solutions, and still often fall short in producing optimal images.

But with today’s high-speed image sensors and data interfaces, there is now an alternative approach that can often improve image quality or produce images that were previously impossible. This approach is called multi-shot or computational imaging, and it relies on capturing a sequence of images taken under different lighting or optical conditions. These images are processed with image processing software, to create an output image that enhances image quality or extracts the features needed for a specific machine vision task.

These computational imaging sequences can be performed at high speeds with most digital cameras and an ordinary PC or processor, so even rapidly-moving parts are supported. By focusing on the image properties most important to a particular machine vision task, computational imaging offers powerful advantages over traditional one-shot imaging.

In your words, what is computational imaging, and why would someone decide to utilize the technology?

Computational imaging (CI) refers to digital image capture and processing techniques that combine computation and optical encoding. Fundamentally, CI relies on data extracted and computed from a series of input images captured under different lighting or optical conditions. There are a few basic principles involved:

· Computation is inherent in the image formation process

· CI combines special lighting and/or optics along with image processing during image capture

· CI typically involves a sequence of images with different illumination for each frame

· CI covers a wide variety of techniques, all designed to output better images or images with unique characteristics

· CI ends with the image acquisition process – it does not involve image analysis

The benefits of CI are very clear. First and foremost, CI permits better or previously impossible images for machine vision systems to be created at lower cost. Forget about iterative attempts to get the lighting and optics right, forget about post-processing to enhance images in software. CI, with its targeted feature extraction, directly outputs the image your vision algorithm needs. This is turn allows you to shorten development time and create superior machine vision solutions.

Whether you need depth information, better color, more image contrast, more depth of field, or even if you’d like to combine lighting techniques or leverage multispectral information, CI allows you to get the image you need, in a very efficient way. Finally, CI allows you to innovate. With CI, system designers can start to think in new ways about creating solutions to difficult imaging problems.

Read the full article at Vision-systems.com.