Teledyne DALSA launch “Linea Lite” line scan cameras

Linea Lite and Linea sizes compared

The “Linea Lite” 2k and 4k line scan cameras provide industry-leading performance in a compact package. Built for a wide-range of machine vision applications, the new Linea Lite cameras feature a 45% smaller footprint than the original Linea and are based on a brand new, proprietary CMOS image sensor designed by Teledyne Imaging. This expands on the success of the Linea series of low cost, high value line scan cameras.

Designed to suit many applications, the Linea Lite offers customers a choice between high full well mode or high responsivity mode, via easy to configure gain settings.

Linea Lite (left) vs. original Linea (right – with lens) (Note: original Linea series also available)
Linea Lite 4k – Linea 4k

The cameras are available in 2k and 4k resolutions, in monochrome and bilinear color. Linea Lite has all the essential line scan features, including multiple regions of interest, programmable coefficient sets, precision time protocol (PTP), and TurboDrive™. With GigE interface and power over Ethernet (PoE), Linea Lite is an excellent fit for applications such as secondary battery inspection, optical sorting, printed materials inspection, packaging inspection, and many more.

Linea Lite Specifications

Download full specifications here.

KeyFeatures:

– 7µm or 14µm pixels

– 2k and 4k resolutions

– Configurable full well

– Precision time protocol

– Selectable 8 or 12-bit output

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1st Vision’s sales engineers have an average of 20 years experience to assist in your camera selection.  Representing the largest portfolio of industry leading brands in imaging components, we can help you design the optimal vision solution for your application.

Types of 3D imaging systems – and benefits of Time of Flight (ToF)

Time Of Flight Gets Precise: Whitepaper

2D imaging is long-proven for diverse applications from bar code reading to surface inspection, presence-absence detection, etc.  If you can solve your application goal in 2D, congratulations!

But some imaging applications are only well-solved in three dimensions.  Examples include robotic pick and place, palletization, drones, security applications, and patient monitoring, to name a few.

For such applications, one must select or construct a system that creates a 3D model of the object(s).  Time of Flight (ToF) cameras from Lucid Vision Labs is one way to achieve cost-effective 3D imaging for many situations.

ToF systems setup
ToF systems have a light source and a sensor.

ToF is not about objects flying around in space! It’s about using the time of flight of light, to ascertain differences in object depth based upon measurable variances from light projected onto an object and the light reflected back to a sensor from that object.  With sufficiently precise orientation to object features, a 3D “point cloud” of x,y,z coordinates can be generated, a digital representation of real-world objects.  The point cloud is the essential data set enabling automated image processing, decisions, and actions.

In this latest whitepaper we go into depth to learn:
1. Types of 3D imaging systems
2. Passive stereo systems
3. Structured light systems
4. Time of Flight systems
Whitepaper table of contents
Download

Let’s briefly put ToF in context with other 3D imaging approaches:

Passive Stereo: Systems with cameras at a fixed distance apart, can triangulate, by matching features in both images, calculating the disparity from the midpoint.  Or a robot-mounted single camera can take multiple images, as long as positional accuracy is sufficient to calibrate effectively.

Challenges limiting passive stereo approaches include:

Occlusion: when part of the object(s) cannot be seen by one of the cameras, features cannot be matched and depth cannot be calculated.

ToF diagram
Occlusion occurs when a part of an object cannot be imaged by one of the cameras.

Few/faint features: If an object has few identifiable features, no matching correspondence pairs may be generated, also limiting essential depth calculations.

Structured Light: A clever response to the few/faint features challenge can be to project structured light patterns onto the surface.  There are both active stereo systems and calibrated projector systems.

Active stereo systems are like two-camera passive stereo systems, enhanced by the (active) projection of optical patterns, such as laser speckles or grids, onto the otherwise feature-poor surfaces.

ToF diagram
Active stereo example using laser speckle pattern to create texture on object.

Calibrated projector systems use a single camera, together with calibrated projection patterns, to triangulate from the vertex at the projector lens.  A laser line scanner is an example of such a system.

Besides custom systems, there are also pre-calibrated structured light systems available, which can provide low cost, highly accurate solutions.

Time of Flight (ToF): While structured light can provide surface height resolutions better than 10μm, they are limited to short working distances. ToF can be ideal for or applications such as people monitoring, obstacle avoidance, and materials handling, operating at working distances of 0.5m – 5m and beyond, with depth resolution requirements to 1 – 5mm.

ToF systems measure the time it takes for light emitted from the device to reflect off objects in the scene and return to the sensor for each point of the image.  Some ToF systems use pulse-modulation (Direct ToF).  Others use continuous wave (CW) modulation, exploiting phase shift between emitted and reflected light waves to calculate distance.

The new Helios ToF 3D camera from LUCID Vision Labs, uses Sony Semiconductor’s DepthSense 3D technology. Download the whitepaper to learn of 4 key benefits of this camera, example applications, as well as its operating range and accuracy,

Download whitepaper
Download whitepaper
Time Of Flight Gets Precise: Whitepaper
Download Time of Flight Whitepaper

Have questions? Tell us more about your application and our sales engineer will contact you.

1st Vision’s sales engineers have an average of 20 years experience to assist in your camera selection.  Representing the largest portfolio of industry leading brands in imaging components, we can help you design the optimal vision solution for your application.

Keys to Choosing the Best Image Sensor

Keys to Choosing the Best Image Sensor

Image sensors are the key component of any camera and vision system.  This blog summarizes the key concepts of a tech brief addressing concepts essential to sensor performance relative to imaging applications. For a comprehensive analysis of the parameters, you may read the full tech brief.

Download Tech Brief - Choosing the Best Image Sensor

While there are many aspects to consider, here we outline 6 key parameters:

  1. Physical parameters


    Resolution: The amount of information per frame (image) is the product of horizontal pixel count x by vertical pixel count y.  While consumer cameras boast of resolution like car manufacturers tout horsepower, in machine vision one just needs enough resolution to solve the problem – but not more.  Too much resolution leads to more sensor than you need, more bandwidth than you need, and more cost than you need.  Takeaway: Match sensor resolution to optical resolution relative to the object(s) you must image.

    Aspect ratio: Whether 1:1, 3:2, or some other ratio, the optimal arrangement should correspond to the layout of your target’s field of view, so as not to buy more resolution than is needed for your application.



    Frame rate: If your target is moving quickly, you’ll need enough images per second to “freeze” the motion and to keep up with the physical space you are imaging.  But as with resolution, one needs just enough speed to solve the problem, and no more, or you would over specify for a faster computer, cabling, etc.

    Optical format: One could write a thesis on this topic, but the key takeaway is to match the lens’ projection of focused light onto the sensor’s array of pixels, to cover the sensor (and make use of its resolution).  Sensor sizes and lens sizes often have legacy names left over from TV standards now decades old, so we’ll skip the details in this blog but invite the reader to read the linked tech brief or speak with a sales engineer, to insure the best fit.

  2. Quantum Efficiency and Dynamic Range:


    Quantum Efficiency (QE): Sensors vary in their efficiency at converting photons to electrons, by sensor quality and at varying wavelengths of light, so some sensors are better for certain applications than others.

    Typical QE response curve

    Dynamic Range (DR): Factors such as Full Well Capacity and Read Noise determine DR, which is the ratio of maximum signal to the minimum.  The greater the DR, the better the sensor can capture the range of bright to dark gradations from the application scene.

  3. Optical parameters

    While some seemingly-color applications can in fact be solved more easily and cost-effectively with monochrome, in either case each silicon-based pixel converts light (photons) into charge (electrons).  Each pixel well has a maximum volume of charge it can handle before saturating.  After each exposure, the degree of charge in a given pixel correlates to the amount of light that impinged on that pixel.

  4. Rolling vs. Global shutter

    Most current sensors support global shutter, where all pixel rows are exposed at once, eliminating motion-induced blur.  But the on-sensor electronics to achieve global shutter have certain costs associated, so for some applications it can still make sense to use rolling shutter sensors.

  5. Pixel Size

    Just as a wide-mouth bucket will catch more raindrops than a coffee cup, a larger physical pixel will admit more photons than a small one.  Generally speaking, large pixels are preferred.  But that requires the expense of more silicon to support the resolution for a desired x by y array.  Sensor manufacturers work to optimize this tradeoff with each new generation of sensors.

  6. Output modes

    While each sensor typically has a “standard” intended output, at full resolution, many sensors offer additional switchable outputs modes like Region of Interest (ROI), binning, or decimation.  Such modes typically read out a defined subset of the pixels, at a higher frame rate, which can allow the same sensor and camera to serve two or more purposes.  Example of binning would be a microscopy application whereby a binned image at high speed would be used to locate a target blob in a large field, then switch to full-resolution for a high-quality detail image.

For a more in depth review of these concepts, including helpful images and diagrams, please download the tech brief.

Download tech brief - Choosing the Best Image Sensor

1st Vision’s sales engineers have an average of 20 years experience to assist in your camera selection.  Representing the largest portfolio of industry leading brands in imaging components, we can help you design the optimal vision solution for your application.