• #Machine Vision

Time-of-Flight vs Stereo Vision - a comparison

The third dimension has benefitted numerous industries—especially factory automation, robotics, logistics, and medicine—by providing further vision technologies and applications.

Two 3D methods in particular have become well established: Time-of-Flight (ToF) and Stereo Vision, which are examined in more detail and compared here. Plus, we compare 2d with 3d.

OEM Automatic stocks Time-of-Flight and Stereo Vision is also available, so you can choose which works for you.

What is the difference between 2d and 3d image processing?

2D

With 2D image processing, the captured image is necessarily always a two-dimensional projection of a three-dimensional object. Depth information cannot be captured with a 2D camera. Depending on the viewing angle, this can result in a different contour of a three-dimensional object in the image. 

With that being said,  shape and depth information is not relevant for many two-dimensional applications.

What is 2D imaging suited for? 

Structure and color analysis, part identification, presence checks, damage or anomaly detection, character recognition, and dimensional accuracy inspection. A prerequisite for these tasks is optimal lighting that produces sufficient contrast in the image.

3D

With 3D images, the height information of a scene is also captured. This means volumes, shapes, distances, positions in space, and object orientations can be determined, or a spatially dependent presence check of objects can be performed. 

As with 2D imaging (and depending on the technology), there are prerequisites such as lighting conditions or surface properties that must be considered for optimal image acquisition.

Despite their differences, there are many applications for which both 2D and 3D technologies are suitable. 

Here, the respective advantages and disadvantages are weighed against common application requirements:

Comparing 3D Technologies

Time-of-flight

Time-of-Flight is a very efficient technology that measures distances to obtain depth data. For this purpose, a light source integrated in the camera emits light pulses that hit the object. The object reflects the light pulses back to the camera.

Using the time required for this, the distance and thus the depth value can be determined for each individual pixel.

As a result, the 3D values for the inspected object are output as a spatial image in the form of a range map or point cloud.

The ToF method also provides a 2D intensity image in the form of gray values for each pixel, and a confidence image that represents the degree of confidence in the individual values.

Facts 

• Does not require contrast or specific features such as corners and edges for 3D capture. The capture can perform almost independently of the intensity and colour of the object, making it easy to separate the object from the background 
• Works with moving objects and can perform up to nine million distance measurements per second with millimetre accuracy
• Less expensive, very compact, and less complex compared to other cameras. This allows for easy installation and integration
• Delivers best results only under certain ambient conditions and for a defined measuring range
• Very dark surfaces run the risk that too little light is reflected for a robust measurement
• Too small a working distance can also limit the method, making ToF overall best suited for medium measurement or depth accuracy

Stereo Vision

Stereo vision works similar to a pair of human eyes.

Depth information is obtained through synchronous images taken by two 2D cameras from different viewing angles. 3D data is then calculated based on extrinsic parameters (the position of the two cameras relative to each other) and intrinsic parameters (such as the optical center and focal length of the lens for each camera). Resulting in camera-specific calibration values.

To calculate the depth information, the two 2D images are first rectified. Then a matching algorithm searches for the corresponding pixels in the right and left images. 

With the help of the calibration values, a depth image of the scene or object can be generated as a point cloud.

The best working distance for this procedure depends on the distance and setting angle of the two cameras and therefore varies.

In comparison with T-O-F

This method does not require an active lighting unit such as light or laser beams. However, it always requires a minimum amount of ambient light, since technically these are two separate 2D cameras.

Suitable for...

Conditions that are difficult for other 3D methods, stereo vision can provide better results. Examples include bright ambient light, overlapping measurement areas, and reflective surfaces.

Why you may not require stereo vision

For surfaces with little structure, the stereo vision method finds too few corresponding features in both images to calculate three-dimensional information. 
These limitations can be overcome by artificially generating surface structures using light. For this purpose, a light projector can be integrated to project a random pattern on the surface.

Which technology suits my application?

Time-of-Flight is especially advantageous in applications requiring: a long working distance, a large measuring range, high speed, and low system complexity, while extreme accuracy is less relevant.

Examples include:

• Measuring objects (volume, shape, position, orientation)
• Factory automation: find, pick, assemble objects; detect damaged objects or stacking errors
• Robotics: determining gripping points for robots; gripping tasks on conveyor belts, bin picking, pick-and-place
• Logistics: packaging; stacking, (de)palletizing; labelling; autonomous driving vehicles (navigation, safety warnings)
• Medicine: positioning and monitoring of patients

Stereo vision already offers high measurement accuracy and is surpassed by sensors with structured light. Suitable for detecting uncooperative surfaces with little structure or applications requiring very high measurement accuracy. 

Examples include:

• Determining position and orientation
• High-precision object measurements (volume, shape, position, orientation)
• Robotics: bin picking, navigation, collision avoidance, pick-up and drop-off services
• Outdoor: measuring and inspecting tree trunks
• Component testing, e.g. damage detection

The need for 3D technology is increasing in many applications, especially when combined with artificial intelligence such as deep learning. 

Interested in Basler’s Time-Of-Flight camera or Stereo Vision and looking for more information on how it can work for your application? Email [email protected] or call 0116 284 9900  for expert advice.