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Novel Pathway to Light Suppresses Kasha’s Rule

October 11, 2016

 

 


A discovery about how some molecules produce light, in apparent contradiction of Kasha’s Rule, could have several applications, from industrial to biomedical. 

To explore the origin of aggregation-induced emission, researchers from the University of Vermont and Dartmouth College assessed the emission properties of a series of BF2–hydrazone-based dyes as a function of solvent viscosity. They found these molecules to be highly efficient fluorescent molecular rotors. 

Further examination of the emission mechanism of the molecules revealed that the emission was not from the S1 state, as would be expected from Kasha's Rule, but from a higher energy state. Fluorescence could be enhanced by restricting the molecular rotor’s rotation and suppressing the internal conversion to the dark S1 state. When placed in a thin liquid, the rotating molecules gave off a weak, reddish luminescent glow. However, when the molecules were put into thicker solvents (in this case, mixtures of glycerol and ethylene glycol), the fluorescent light from the molecular rotors, instead of becoming weaker, glowed brightly in a vivid green color nearer the blue end of the spectrum. 

The paddle-shaped part of the rotor must be able to rotate freely in order to activate the chemical pathway that allows it to give off heat energy; but in a thick solution this rotation is suppressed. The thicker the solution, the less the molecular paddles rotate; and the less the rotation, the more light can be emitted. 

The phenomenon led the researchers to propose that suppression of Kasha's Rule was the photophysical mechanism responsible for emission in both the viscous solution and the solid state. The team has called their discovery Suppression of Kasha's Rule, or SOKR. 

"One way to understand SOKR is to think about a water slide with two outlets where one outlet is located far above the pool and the other is located at the level of the pool," said professor Matthew Liptak. "In low viscosity solutions like water, the paddles rush all the way to the bottom outlet and enter the pool without a splash. In high viscosity solutions like maple syrup, the paddles are slowed down, allowing some to spill out the top outlet creating a waterfall or, in the case of light-emitting molecular rotors, bright green light." 

The novel pathway to creating light may have practical use. 

"The compound we found is very bright, and due to its viscosity sensitivity, may have a multitude of applications," said researcher Morgan Cousins. "We see uses for these kinds of molecules from industrial materials to new kinds of LEDs to biomedical imaging."University of Vermont doctoral student Morgan Cousins holds up a sample of a solution of strange rotor molecules made from boron-based dye. Led by UVM chemistry professor Matt Liptak (on left), she was part of a team that tested the dye and discovered how the molecules can release a bright fluorescent glow--it's a new method to create light. Courtesy of Joshua Brown.The SOKR molecules are not safe for use in a human, but the team is currently hunting for similar "bio-compatible" compounds, Liptak says, that could be incorporated into a medical dye or other test where they would glow brightly in more viscous parts of a cell and less in more watery parts. The molecules could be applied as a sensitive diagnostic tool because they precisely change the amount of light they emit based on the thickness of the solution in which they are placed. 

Mvotem is a professional manufacturing company that provides professional manufacturer of optical products for the industrial, military and scientific research, medical equipment, machinery and equipment, colleagues participating in outsourcing, specialized custom precision parts company, the major markets: China, Italy, USA Britain, Japan, Korea and so on. 


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Dymax Named Top Connecticut Tech Company

October 9, 2016

The Connecticut Technology Council has named UV-curable adhesive equipment developer Dymax Corp. as one of the fastest-growing technology companies in the state with a spot on the Marcum Tech Top 40 list. 

For the fifth year in a row, Dymax was recognized as a technology leader in the advanced manufacturing category. The council cites Dymax’s annual revenue growth of at least $3 million, as well as growth in each of the preceding four years. 

President Steve LaCroce accepted the award at a ceremony at the Oakdale Theatre in Wallingford, alongside 39 other companies. 

Dymax develops innovative oligomer, adhesive, coating, dispensing and light-curing systems for applications in a wide range of markets.

Mvotem is a professional manufacturing company that provides professional manufacturer of optical products for the industrial, military and scientific research, medical equipment, machinery and equipment, colleagues participating in outsourcing, specialized custom precision parts company, the major markets: China, Italy, USA Britain, Japan, Korea and so on.

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CONTACT US

Kunshan Bao Yi Road No. 99 east 5 floor


Tel:+86(0)512-50136097 
Fax:+86(0)512-50156446

Email:Sales@mvotem.com

Luxtera Ships One Millionth Transceiver Product -Mvotem

September 27, 2016

 

Semiconductor provider Luxtera Inc. has announced the shipment of its one millionth silicon photonic parallel single-mode fiber four-lane transceiver product. 

The patented technology blends the long reach capabilities of single-mode fibers with low-cost transceivers. This combination is critical for the cost-effective scaling of cloud computing data centers. 

“This is a huge milestone for the optics industry and an exciting achievement for Luxtera,” said Greg Young, president and CEO of Luxtera. “With over 1 million units deployed, sweeping design wins and 100-Gbps PSM4 shipping in 100K+ volumes, it is clear that our products are at the center of the industry’s $5 billion optical super cycle. Passing this milestone signals that our customers have embraced our vision, including volume orders for solutions that offer long reach and low cost with best-in-class performance.” 

Luxtera was a founding member and drafter of the 100G-PSM4 Multi Supplier Agreement (MSA) in 2014, the first standard to enable silicon photonics interoperability with legacy DML Optical modules for PSM4 fiber without compromising the cost benefits of silicon photonics. This widely accepted MSA has the support of dozens of companies with PSM4 product offerings and is being deployed at scale by the major cloud computing operators.

Radiotherapy Lens -Mvotem

September 22, 2016

 

Mvotem
Resolve OpticsResolve Optics Ltd. has announced a 24-mm-diameter fixed nonbrowning lens for radiotherapy. 

Using cerium-doped glasses, Resolve Optics produced a compact f/2.8 lens able to withstand long-term exposure to radiation up to a dose of 100 million radians without discoloration. This new lens is enabling improved precision radiotherapy treatment of tumors. 

The lens is able to withstand and precisely focus high levels of radiation produced by synchrotron devices. 

AIS Becomes Fanuc Integrator - Mvotem

September 17, 2016



Advanced manufacturing company Active Industrial Solutions (AIS) has become an authorized Fanuc System integrator. 

“Fanuc is very excited to have AIS recently join our authorized system integrator network,” said Norbert Boch, account manager at Fanuc. “We look forward to the vision-guided expertise AIS can provide our mutual customers in a wide range of industries.” 

Fanuc offers a range of products and services for robotics, CNC systems and factory automation solutions. 

“AIS is honored to become an authorized Fanuc System integrator,” said Chuck Curtiss, president of AIS. “Adding value is an integral part of the AIS core mission. Having the distinction as a Fanuc System integrator is a natural fit to meet our customer needs.” 

mvotem is a professional manufacturing company that provides professional manufacturer of optical products for the industrial, military and scientific research, medical equipment, machinery and equipment, colleagues participating in outsourcing, specialized custom precision parts company, the major markets: China, Italy, USA Britain, Japan, Korea and so on. 

 
 


CONTACT US 

Kunshan Bao Yi Road No. 99 east 5 floor 

Tel:+86(0)512-50136097 
Fax:+86(0)512-50156446 

Email:Sales@mvotem.com 

Ultrahigh-Resolution Microscope Images Whole Cells in 3D - Mvotem

September 12, 2016



A novel superresolution nanoscope allows 3D imaging of an entire mammalian cell and its cellular constituents at a resolution that is 20 to 50 times higher than conventional microscopy, with imaging depth improved approximately tenfold over state-of-the-art iPALM and 4Pi-SMSN implementations. Until now, resolving details at this level was only possible using electron microscopy, which requires samples to be treated. 

The whole-cell 4Pi single-molecule switching nanoscope, called W-4PiSMSN, allows volumetric reconstruction with 10- to 20-nm isotropic resolution of approximately 10-μm-thick samples. The novel nanoscope permits ultrahigh-resolution 3D imaging of virtually any subcellular structure, allowing researchers to resolve details smaller than the wavelength of light. 
 


Using a new 3D superresolution instrument, researchers captured this visualization of a "primary cilium," the antenna of the cell. Courtesy of Huang et al./Cell. 


The W-4PiSMSN incorporates deformable mirrors using two objectives, one above and one below the sample, and uses a set of algorithms to pinpoint molecular positions of proteins deep inside cells, resolving features deep below the surface of the sample. 

Researchers have demonstrated the wide applicability of W-4PiSMSN by imaging complex molecular architectures ranging from bacteriophages (viruses about 50 nm in diameter) to nuclear pores, cilia and synaptonemal complexes in large 3D cellular volumes. The development of W-4PiSMSN extends the application range of 4Pi-based SMSN to the imaging of organelles that span large volumes, exemplified by the mitochondrial network, the nuclear envelope, and synaptonemal complexes, which researchers were able to capture in virtual entirety. 
 


The technology was used to visualize a mouse spermatocyte, revealing with unprecedented clarity the "twisting paired lateral elements" of synaptonemal complexes, which link chromosomes together. Courtesy of Huang et al./Cell. 
The research team included researchers at Purdue University, Yale University, the University of Cambridge, the Jackson Laboratory, Howard Hughes Medical Institute and the University of Oxford. 

The advance could reveal biological phenomena never before seen, bringing novel medical insights. 

"One goal is to further push the envelope in the direction of live-cell and tissue imaging, two major roadblocks of modern superresolution techniques, and therefore allow visualization of cellular functions live in their physiological conditions at the nanoscale,” said Fang Huang, professor of biomedical engineering at Purdue. 

"We are interested in using our developments to study the cytokinetic apparatus, a core machinery during cell division," he added. 

W-4PiSMSN is a versatile and powerful tool that promises a new perspective on how proteins distribute across entire organelles throughout whole cells, an as yet unmet challenge in cell biology.

Mvotem is a professional manufacturing company that provides professional manufacturer of optical products for the industrial, military and scientific research, medical equipment, machinery and equipment, colleagues participating in outsourcing, specialized custom precision parts company, the major markets: China, Italy, USA Britain, Japan, Korea and so on.

 

CONTACT US


Kunshan Bao Yi Road No. 99 east 5 floor


Tel:+86(0)512-50136097 
Fax:+86(0)512-50156446

Email:Sales@mvotem.com

Playing to Type: Choosing the Right Class of Lens for Machine Vision

September 8, 2016

Mvotem Optics

Machine vision systems have one general task: to collect and process optical information so measurements, observations or decisions can be made without direct human intervention. In other words, machine vision systems are supposed to augment or serve as surrogates for people in specific industrial roles. But machine vision systems lack one essential component of human systems: They don’t have brains.

Our brains allow us to interpolate and extrapolate poor and contradictory visual information to make decisions about reality. Because machine vision systems lack that powerful information processor, they don’t function well with poor or inconsistent visual information. That means you need to design your machine vision system to meet specific performance requirements and to provide high-quality, consistent images. And it all starts with the optics.

As you evaluate your system requirements, you’ll be driven to decide on the class of lens for your imaging system. You should be aware that you have three lens options: endocentric, telecentric or hypercentric. Endocentric lenses produce images with the same kind of perspective as the human eye – these are standard fixed-focal-length lenses. Telecentric lenses eliminate perspective errors (also called parallax), and hypercentric lenses invert normal perspective to see nearly the entire surface of a three-dimensional object. Although all three lens classes can be defined in terms of their optical design, an example can more easily illustrate how characteristics of each class can provide specific performance benefits. This hypothetical example will illustrate the characteristics that will drive you to select an imaging lens from a particular class. 

Optimizing factory performance

Whether your machine vision system is being used for process control or quality inspection, it will have a specific task. For example, say you’re working in a syringe-manufacturing factory. You might have to verify the placement and number of syringes before sealing the packages. An easy enough job for a person – but a bit slow and mind-numbing. So you want to replace that function with a machine vision system.

This particular task – counting and verifying placement of syringes within a package – does not require great precision. You’ll have to define the image parameters of a syringe, but you can do that with edge-detection or some other pattern-recognition algorithm. It won’t matter to that algorithm whether the syringe image is 17 or 22 pixels across. Why is that important? Because an endocentric lens acts just like your eye: Objects that are farther away appear smaller in the image. With an endocentric lens, the physical size of the syringe image on the detector will be different for syringes at different distances from the lens.

For tasks that don’t require precise measurements, such as the syringe-counting application, you can most often comfortably use an endocentric lens. If you need to verify that bar codes are legible on a package of razors, or that the color of your cereal boxes is within an acceptable range, an endocentric lens is usually the best option (Figure 1).

Most standard fixed-focal-length lenses are endocentric, which is good for general imaging applications.

Remember, though, that just because your application might not need metrology-class imaging doesn’t mean you don’t need high-quality images. A lens that distorts can make it difficult for your pattern-recognition routine to consistently identify syringes, particularly at different places within the field of view. Similarly, a lens with illumination/resolution falloff in the corners, or with poor contrast at the spatial frequency of your bar code, will make it difficult to verify legibility; a lens with lots of chromatic aberration will make it problematic to test the color of your cereal boxes. Put another way, just because you can use a traditional endocentric-class lens doesn’t mean you can use a poor-quality lens.

Going telecentric

Imagine now that your first machine vision project at the syringe factory has gone so well that you decide to use machine vision elsewhere. Assume that another task at your factory is to verify that the internal and external diameters (IDs and ODs) of your syringes are within specification – all along the length of the barrel. Right now this is done by a technician randomly selecting syringes from the production line and measuring the ID and OD of each by hand with a micrometer.

Choosing an endocentric lens for this task will create problems because endocentric lenses image with the same kind of perspective as the human eye. For example, if you decide to image the syringes as they lie flat on a conveyor belt, their distance from the imaging lens will vary from syringe to syringe – and even from one end of the syringe to the other – as they bounce along the belt.

If you decide to image the syringes on end, looking down the barrels, the problem becomes even more difficult. Why? Because even if you line up the barrels perfectly with the optic axis of your lens, you still have the problem that nearer objects appear larger than more distant ones. Specifically, the closest ends of the syringes will produce circle images that appear larger than the circle images of the farther ends of the syringes. Another way of saying this is that the magnification of endocentric lenses is a function of object distance. For this function, you will need a lens where the magnification does not vary with object distance – the telecentric lens.

Telecentric lenses create their images from light that comes right along the optic axis. They come in three varieties: object-space, image-space and bilateral (or double) telecentricity. Object-space telecentric lenses have their entrance pupil at infinity, image-space telecentric lenses have their exit pupils at infinity, and bilaterally telecentric lenses have both entrance and exit pupils at infinity. For typical metrology applications, you’ll want an object-space or bi-telecentric lens (Figure 2).

The complex design of telecentric lenses can create accurate and consistent images for metrology.

Those details of optical design have one very practical effect: The magnification in an object-space telecentric lens does not vary with object distance. So, when you image along a syringe, you will see the ID and OD of the barrel along the entire length simultaneously. If there’s a “bump” anywhere along the length of the barrel, the image will show it. In addition, once you calibrate your lens, you can accurately and consistently measure diameter directly from the images.

Shifting perspective with hypercentric lenses

Your success at addressing the packaging and metrology problems was so dramatic that you’ve decided to address another inspection problem with a machine vision system: The syringe markings all around the top of the perimeter of the barrel need to be consistent and clear. Currently, you have a technician pull some random samples and spin them around to examine the markings all around the syringes. You could use an endocentric imaging lens to acquire images as you rotate the syringe, but it would be a lot more convenient if you could image the entire outside of the barrel in one simple acquisition. That’s a job that a hypercentric lens is made to address, and it allows you to use one lens instead of two, three or even four endocentric lenses.

When you look at the field of view of an endocentric lens, it’s a cone that diverges from the front of the lens. A telecentric lens has a cylindrical field of view. A hypercentric lens goes a step further – it’s a cone that converges from the front of the lens. For example, at 10 cm away, a 6-cm diameter endocentric lens could have a field of view that’s 12 cm wide, a telecentric lens would have a field of view about 6 cm wide, and the field of view of a hypercentric lens could converge to a point at that same 10-cm distance (Figure 3).

Figure 3. (a) Hypercentric lenses invert normal perspective to simultaneously image the top and sides of objects within the working area. (b) Here, a die is imaged using (bottom) a hypercentric lens and (top) a fixed-focal-length lens.

As you might expect from that description, the perspective of a hypercentric lens is exactly the opposite of that of an endocentric lens. With an endocentric lens, nearer objects create larger images than more distant objects, while in a hypercentric lens, nearer objects create smaller images than more distant objects. In practice, this has the effect of transforming an on-axis cylinder into an annular disk at the image plane.

For example, with your syringe, the innermost circle of the image will be the near end of the syringe, while the far end of the syringe will be projected onto a larger circle in the image. The cylindrical surface of the syringe at a given distance from the lens is projected onto a circle of a specific radius on the image plane. If your syringe has a colored band halfway down its length, the band will appear as a circle on the image plane. With one acquisition, you can image the entire outer circumference of the syringe. If you insert a spacer between a hypercentric lens and a detector, you create a borescope capable of imaging the interior of a cylinder with the same kind of circular projection.

The rest of the story

The examples given here illustrate situations appropriate for different types of lenses. That’s just the start of specifying your machine vision system. You’ll want to evaluate the resolution you need, the wavelengths you want to acquire, the field of view of your scene, the detector geometry, the image acquisition rate, the scene illumination and other factors. But understanding the fundamental characteristics of endocentric, telecentric and hypercentric lenses gives you a head start on an efficient machine vision system. If you are in a situation where the unique features of telecentricity or hypercentricity match your imaging needs, you can streamline the rest of your system design.

Meet the author

Nicholas James is the product line manager for imaging at Edmund Optics in Barrington, N.J.; email: njames@edmund optics.com.

Limitations of telecentricity and hypercentricity

You might be tempted to take advantage of the inherent accuracy of telecentric lenses for all your applications – after all, why not get the most accurate, consistent measurements out of every image? But telecentric lenses aren’t always the optimum choice.

The narrow acceptance angle of telecentric lenses means that the maximum linear field of view can be no larger than the lens diameter (often 10 to 20 percent smaller). If your object is large, the lens must be equally large. But as the lens diameter goes up, so do the cost and weight of a telecentric lens. 

Telecentric lenses also have a relatively limited working distance. That’s also an issue of lens diameter (and cost), because the diameter of a telecentric lens grows as the working distance increases.

Hypercentric lenses have similar issues. The field is smaller than the lens diameter, and the working distance is also relatively small. The usable portion of the converging-cone field of view of a hypercentric lens is called the “near-view cone” or “working area,” and it’s typically on the order of tens of millimeters.

So it’s best to consider telecentric and hypercentric lenses as valuable and efficient tools for unique imaging applications – tools that can justify their higher cost with increased performance and efficiency where warranted.

CCTV Camera Lenses Explained -Mvotem

September 6, 2016

Machine vision

Mvotem CCTV Telephoto Zoom Lens in Global and China market, focuses on top manufacturers in global and China market, involving CCTV Telephoto Zoom Lens price of each type, production, revenue and market share for each manufacturer. 

A CCTV lens is a camera’s window on the world. Simon Lambert explains what you need to know about CCTV lenses. 

The old advice that “a chain is as strong as its weakest link” is certainly applicable to your CCTV. That’s why you must take care at every point in your system. These small, hidden, unsexy devices are often where corners are cut. People fail to appreciate how poor choices let them down. It isn’t difficult to make good choices. 


Every lens should create a clear image of the scene for the camera to turn into video. How clear is “clear”? Your Operational Requirement details the job your CCTV must satisfactorily perform. Each lens must be a strong enough link in your CCTV chain to make sure it can ‘pull its weight’, so let’s understand your choices. 

Lens fittings 
To begin, how can you fit any lens to any camera? ‘C’ and ‘CS’ mount devices all have the same screw thread. Some older or larger lenses are C-mount so will fit on both C and CS-mount camera bodies (with a 5mm adaptor ring). 

Most recent small lenses are CS-mount so are fine on CS camera bodies but will never achieve focus if used on a C-mount camera. Be careful. 

Basic lens set-up 

The simplest CCTV lens is a piece of glass (or plastic) to focus the light from the outside world onto the camera’s imaging sensor. 

This lens’ only adjustable mechanism is its focus-ring, part of the barrel body, which you turn until your image is as clear as possible. Incidentally, use the sharpest test monitor you can. For instance, black & white tubed monitors can be much sharper than colour LCDs. The amount of light let through to the camera cannot be controlled by this simple lens. 

Upgrading to a lens with a manually adjustable ‘iris’ is only a benefit during set-up, so both are best suited to scenes where lighting is constant. To a limited degree, an automatically adjusting electronic shutter in the camera might accommodate changing brightness. However, in scenes where it varies significantly, such ‘electronic iris’ features are better replaced by an ‘auto-iris’ lens. 

Auto-iris lens 

Automatic iris lenses are controlled by the camera to make sure that the right amount of light gets through to the imaging chip. 

Too little and the iris opens up. Too much and the iris shrinks. 

During CCTV set-up this lens/camera automatic level control (ALC) needs tweaking so as to aim for the desired brightness. The smallest auto-iris lenses have few electronics inside because the driving amplifier is in the camera. 

These ‘direct drive’ (DD) lenses have a built-in cable usually carrying a widely-used square 4-pin connector plug which connects to the camera. The video level adjustment is done by twiddling a rotary ‘pot’ (potentiometer) on the camera’s body or using its internal software menus. 

More sophisticated auto-iris (AI) lenses contain their own amplifier which provides two pots. One is for adjusting video level, as described above. The other is called ‘peak/average’ and when turned fully to ‘peak’ it considers the brightest part of the scene when controlling the iris. When turned fully to ‘average’ it considers the whole scene’s brightness when controlling the iris. 

This latter case is most common in normal use, but the peak function can be vital where brightest areas must retain details, even at the expense of shadow details, especially under night time lighting. 

Traditionally, the heavier auto-iris lenses contained servo motors to drive the iris mechanism, especially inside large zoom lenses. Small direct drive lenses use lightweight ‘galvometric’ electromagnetic actuators for the iris, as do some AI lenses now. 

Lens speed – the F-stop 

A large iris delivers more light into the camera, obviously. Rather unhelpfully, however, the more ‘telephoto’ the lens the less light will get through. So how do we quantify the practical effect of these contradictory factors? 

Every lens has an ‘F-stop’ number describing its maximum capability. For instance, F1.0 can pass four times as much light than an F2.0 lens. Half the F-number, quadruple the light! 

Smaller F-numbers are better, which is particularly important for low-light CCTV performance. Wide-angle lenses commonly range from F0.8 to F1.8 while zoom lenses often range from F3.5 upwards, which means much less light gets into the camera. 

Ramping 

Be aware that such a zoom lens claiming F3.5 will give this at its wide-angle position, but when fully zoomed it could drop to F8.0! This is called ramping and zoom lenses that minimise it cost a lot more money than budget lenses that only look good on paper. 

Better contrast 

Better quality optical elements will give you better contrast in your images, and fewer colour fringes around object’s edges (chromatic aberration). 

With better resolution tiny details will be clearer and brighter, especially at the edges of the image where all lenses have imperfections, and straight lines will show less curvature (geometric distortion). 

‘Aspherical’ optics are particularly finely crafted to maximize light transmission, hence impressive F0.8 capabilities. 

Also, infrared in daylight and electric light can focus in a different place to visible light thereby defocusing your image. IR-corrected lenses reduce this effect. 

A poor lens on a good camera is a waste of a good camera. 

Video surveillance resources 

Guide to CCTV Technologies 
Setting your objectives and requirements 
3 key elements to a video surveillance system 
Camera lenses explained 
CCTV Lighting Guide 
VMS Video Management Systems explained 
Field of view 

The field-of-view (FoV) your lens provides is fundamental to your meeting the Operational Requirement. The focal length of any lens is measured in millimetres (mm). 

In CCTV where a camera’s chip can be, for instance, 1/3-inch format, a ‘wide-angle’ 2.8mm lens offers a horizontal field-of-view around 74 degrees; a ‘standard’ 8mm lens offers around 30 degrees, whereas a ‘telephoto’ lens of 50mm narrows the FoV down to less than 5 degrees. 

The shorter the focal length, the wider the view. Megapixel cameras may have 1-inch format sensors meaning that large professional photographic lenses are used. 

Fixed focal length lenses, known as ‘prime’, have no FoV adjustment but can perform very well owing to their simplicity. 

Adjustable ‘fixed’ lenses 


The practicalities of CCTV installation can seek adjustable ‘fixed’ lenses. These are called varifocal and offer, for instance, a range of 10mm to 40mm which is manually adjusted during installation prior to focusing. 

The downside to this versatility is often lower optical quality than a correctly selected prime lens. Motorising a zoom lens adds more remote control versatility to its applications. 

Bigger lenses in large motorised zooms make them heavy, but greatly improve low-light performance. Incidentally, if you intend to drive such lenses to pre-programmed zoom and focus positions, e.g. in response to an alarm trigger, then make sure the servo mechanisms are built in. 

Zoom lenses are often advertised by their zoom ratio, e.g. 30:1, which seems impressive but actually tells us very little of practical use. Its shortest and longest focal lengths are what we need to know to make sure our desired FoVs will be achievable. 

Zoom-tracking 

Setting up requires the right tools and understanding, particularly the camera’s back-focus adjustment for correct zoom-tracking which is necessary for your image to stay in focus while zooming from maximum telephoto to wide-angle. 

So many don’t owing to poor work by CCTV technicians, so should be checked. 

Lenses are impressive feats of technology. Many modern lenses can perform amazingly well. Poor lenses are, however, weak links that undermine the strength of your CCTV. The price of good lenses is tiny when compared with their value in your system.

No tipping point in sight for machine vision

September 5, 2016

 

Machine vision sales growth stuck in single digits despite advent of Industry 4.0 

Very sophisticated sensor technology is key to the next phase in the development of the “internet of things.” Machines, vehicles and devices will need to be able to “see” in order to collect valuable data, avoid collisions and spot when something has gone wrong. 

Yet sales of machine vision technology are fairly modest and growing at a fairly sedate pace. In 2015, the German machine vision industry, which is in the vanguard of this sector, achieved sales of 2 billion euros ($2.2 billion) – a rise of 9% compared to the previous year, according to figures recently released by the industry association VDMA. 

Although sales have more than doubled in the past 10 years, according to the VDMA, there is no sign yet of the exponential growth that might be expected as machine vision moves beyond simply inspecting finished products for defects to a much wider range of applications. In theory at least, the market should see a dramatic boost as the IoT expands and the Industry 4.0 concept gains traction. Machine vision is a pivotal enabling technology for Industry 4.0, which involves extensive data capture and analytics to continually optimize the operation of factories. 

Slight slowdown in 2016? 

Machine vision

If there is a tipping point ahead for the machine vision market, it isn’t going to happen in 2016. The VDMA forecasts that the German machine industry’s sales will rise just 8% to 2.2 billion euros in 2016. That forecast is based on 15% growth in Asia, 14% in America and just 5% in Europe. 

“There is greater caution about developments in Europe,” the VDMA said. “Relevant risks and opportunities include future developments in the price of raw materials, exchange rates, and last but not least, the effects of political crises.” 

Independent analysts also see steady, rather than spectacular, growth ahead. The global machine vision market is set to grow from $8.08 billion in 2015 to $12.49 billion by 2020, at a compound annual growth rate of 9.1%, according to RnR Market Research. 

Such forecasts may reflect the fact that the manufacturing sector is inherently conservative. Few companies are prepared to overhaul existing production lines to implement complex Industry 4.0 systems. Because the costs of down time are too great, self-optimisation technologies are likely to be adopted primarily by new factories, curbing the pace of adoption. 

Looking beyond the factory floor 

Still, the machine vision sector should be seeing strong growth in nonindustrial applications, such as driver support systems, building and land surveillance, conservation, logistics, and medical technology. The VDMA said Germany’s machine vision sales to nonindustrial sectors grew an average of 16% per year between 2011 and 2015. 

Ongoing improvements in the technology, such as the growing sophistication and flexibility of systems that can see in 3-D and the employment of machine learning techniques, could expand the market further still. The upcoming VISION trade fair, held by the VDMA in November in Stuttgart, Germany, should help clarify whether there is a tipping point ahead. One of the key talking points is likely to be the falling cost and improving processing speed of 3-D machine vision systems. 

Among the 400 exhibitors will be some notable debutants. German technology company Bosch, for example, will be present for the first time. It plans to showcase its APAS Inspector solution for smart manufacturing. Designed for human-machine cooperation, the system can be configured to stop working if a human gets too close and start again once the human is out of the way. Bosch said APAS, which uses 3-D imaging, can inspect matte or glossy surfaces and give completeness checks, as well as carry out microcrack and dimensional inspection. 

In a news release issued by the VISION organizers, Jana Bartels, product manager for 3-D/ToF at Basler, a machine vision company based in Ahrensburg, Germany, added: “There is growing interest in 3-D cameras, for example, for process automation and monitoring, to simplify the control of robotic systems, and to optimize, and increase the security of, man-machine interfaces.” She highlighted a collaborative project between Jungheinrich and the Hanover Institute for Integrated Production with Basler, and Götting KG and the University of Lübeck to create a “high-reach forklift truck that understands human language and uses 3-D machine vision to interpret gestures.” 

That forklift truck is likely to be a harbinger of things to come – the rise of robots equipped with artificial intelligence could yet give the machine vision market the major fillip it has been waiting for. 

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Mvotem - Machine Vision System Market: 2016 Industry Growth with Key Manufacturers Analysis

September 1, 2016

Machine vision uses machines to measure and judge instead of human eyes. Typical machine vision systems can be divided into PCB machine vision system and embedded machine vision system (smart cameras). 

In 2015, the global machine vision market size approximated USD4.2 billion, up 10.5% year on year. The United States is the world's largest machine vision market with the share of above 50%, followed by Japan. 

China machine vision industry started late with a small market base, but grows by leaps and bounds (it has been in a rapid development period since 2009), and has become the third-largest machine vision market following the United States and Japan. In 2015, Chinese machine vision market was worth RMB2.2 billion (about USD350 million), accounting for 8.3% of the global total and growing at 22.2% (higher than the global average). During 2016-2020, Made in China 2025 will boost Chinese machine vision market to maintain the growth rate of around 20%. 

Chinese machine vision system is mainly applied in semiconductor and electronic manufacturing (accounting for 46.4% in 2015), especially SMT, AOI/AXI devices and connector detection. In addition, automobiles and pharmaceuticals consumed 10.9% and 9.7% respectively of machine vision system in 2015. 



Complete Report Spread across 126 pages and 196 Charts. Now Available. More Details about this Report available at http://www.chinamarketresearchreports.com/contacts/inquire-before-buy.php?name=115330 



Most foreign machine vision vendors enjoy superiority in the industry chain ranging from core components (light source, lens, cameras, frame grabbers, image processing software, etc.) to system integration, but Chinese counterparts do not have advantages in terms of software and hardware (they primarily purchase hardware), therefore they mostly focus on machine vision system integration and equipment manufacturing. 

Currently, machine vision vendors in the United States and Japan act as the world's absolute leaders. Among them, Japan Keyence ranks first in both industrial scale and market share (market share: 12.7% in 2015). Unlike the international market, China machine vision industry has not formed a distinct competitive pattern yet. Therefore, a number of listed companies embarked on the layout of machine vision business in 2015 in order to seize the machine vision market. 

In May 2015, Maxonic Automation Control and Denmark Scape collaborated to make a layout for 3D vision and robotics business. 

Ningbo Cixing acquired 68% stake in Suzhou Dinnar (main business: automated assembly lines, vision inspection equipment) in April 2015 and will develop machine vision controllers via Suzhou Tuce, a subsidiary of Suzhou Dinnar. 

In June 2015, Hikvision launched industrial stereo cameras and area array cameras suitable for robot positioning and guide of intelligent factories, product defect detection, etc. 

The report focuses on the following aspects: 

Global machine vision development environment, market size, market structure (the market in major producing countries), patents, competitive pattern, etc. 
China’s machine vision development environment, market situation, patents, cost structure, competitive pattern, development trends, etc. 
Market overview, major vendors and the like of major machine vision components (light source, lens, industrial cameras, frame grabbers, image processing software, system integration, etc.). 
Main machine vision applications (semiconductor and electronic manufacturing, automotive, pharmaceutical, food packaging, etc.). 
Operation, layout in china, machine vision business and so forth of 8 global and 12 Chinese machine vision vendors. 
 

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Tel:+86(0)512-50136097 
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