Yes, all Basler cameras except the L104k (with 1k and 2k resolution) fulfill the RoHS rules and regulations according to the environmental directive 2002/95/EC.
Frequently asked questions
Result
| Question | Category |
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| Are Basler Cameras RoHS compliant? |
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| The pylon viewer in pylon4linux 2.3.3 is having problems starting up. What can I do to stop this? In pylon4linux 2.3.3, you may get the following error messages when trying to run the pylon viewer (or the SpeedOMeter), even though the PYLON_ROOT and GENICAM_ROOT_V2_1 environment variables and the LD_LIBRARY_PATH were correctly exported:
"PylonViewerApp: symbol lookup error: /usr/lib/libQtNetwork.so.4:
undefined symbol: _ZN14QObjectPribate15checkWindowRoleEv" In this case, it seems that some of the Qt libraries, i.e., libQtNetwork, were loaded from "/usr/lib" while other Qt libraries were loaded from the local pylon "pylon/bin" folder. Due to a mismatch in the different Qt versions, the pylon viewer will fail to start.
To fix the problem, you must remove (e.g., save them as a backup in a folder on the desktop or delete them permanently) all local Qt libraries and the correspondent links used by the pylon viewer that were placed in "pylon/bin".
The libraries and links (a total of 16) that should be removed are:
libQtCore* libQtGui* libQtNetwork* libQtXml* |
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| What is binning?
What is binning?
What is binning? Binning in CCD Cameras
Binning increases the camera's sensitivity to light by summing the charges from adjacent pixels in the CCD sensor into one pixel. There are three types of binning available: horizontal binning, vertical binning, and full binning. With horizontal binning, pairs of adjacent pixels in each line of the sensor are summed (see the drawings below). With vertical binning, pairs of adjacent pixels from two lines in the sensor are summed. Full binning is a combination of horizontal and vertical binning in which four adjacent pixels are summed. ![]() Using horizontal or vertical binning generally increases the camera's sensitivity by up to two times normal. Full binning increases sensitivity by up to four times normal. On some camera models, using horizontal or full binning increases the camera's maximum frame rate (this is not true for all cameras and depends on the architecture of the sensor used in the camera).
With horizontal binning active, horizontal image resolution is reduced by half, for example, if a camera's normal horizontal resolution is 1300, with horizontal binning active, this would be reduced to 650. With vertical binning active, vertical image resolution is reduced by half, for example, if a camera's normal vertical resolution is 1030, with vertical binning active, this would be reduced to 515. When full binning is used, both horizontal and vertical resolution are reduced by half.
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| Is there a way to build applications based on Basler pylon without purchasing Microsoft Visual C++ Studio? Some users of Basler's Pylon 2.0 software may want to build their own applications without the need to buy Microsoft Visual C++ Studio. Application notes are available that describe a way to build pylon based applications for free using Microsoft Visual C++ Express and the Microsoft Platform SDK.
Click here to download the application notes. |
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| When I create applications for Basler cameras on my development machine, my Visual Studio 8 application runs fine. On the customer's equipment, however, my application fails to start due to configuration errors. What's wrong with my application? As you may know, applications created with Visual Studio need some Microsoft runtime libraries available to function properly (some dependencies, for example, are the CRT, MFC, and ATL runtime libraries). With Visual Studio 6, the only thing you needed to do to distribute these libraries (DLLs) was to simply place a copy of them in the same folder as your application's executable. With .NET, Microsoft introduced the concept of "assemblies". Assemblies contain all of the required runtime libraries as well as something called "manifest" files. Manifest files contain information about which version of which runtime library is explicitly needed by the application. The MSDN includes a lot of information about assemblies and about deployment of applications created with VS .NET.
The simplest way to redistribute the Microsoft runtime libraries is by providing the vcredist_x86.exe redistribution package together with your application. You will find vcredist_x86.exe within the following Visual Studio 8 program folder: <PROGRAM FILES>\Microsoft Visual Studio 8\SDK\v2.0\BootStrapper\Packages\vcredist_x86 When vcredist_x86.exe is executed on the target machine, all required Microsoft runtime assemblies will be installed in the "global assembly cache" (the WinSXS folder). Your application will then be able to find all of the required C++ runtime libraries, and it will start properly. Q: Fine, this works for release builds, but I need to deploy a debug build of my application. What should I do?
A: All required debug versions of the runtime libraries come with Visual Studio. According to the Microsoft Visual Studio license agreement, redistribution of the debug versions of the VS runtime libraries is not allowed. To run a debug build of your application, the target machine must have the same version of Visual Studio installed that you used when developing the application. |
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| Which 32 bit and 64 bit Linux distributions does pylon for Linux support? Until recently, pylon for Linux officially supported only OpenSuse 10.3 and Ubuntu 8.04. Packages were available that allowed these distributions to be installed without the need to also install the additional or older libraries that pylon depends on. For distributions other than or newer than those officially supported, however, you needed to install additional libraries such as libXalan-c-110 (not for pylon-*-bininst-* packages), libXerces-c-27 (not for pylon-*-bininst-* packages), or QT 4.3.1 in order to make pylon work. But for these unsupported distributions, the installation of older libraries may "pollute" a system and cause other applications to not work correctly. In addition, once these older libraries are installed, the user must make sure that pylon is correctly linked to the libraries.
All of this made it quite difficult to use pylon on Linux distributions that were not officially supported.
To solve all of these problems, reworked pylon 2.3 packages for 32 bit and 64 bit Linux distributions have been created, and these new packages include all of the libraries that pylon depends on. The packages are called "pylon-2.3.3-1337-32.tar.gz" and "pylon-2.3.3-1337-64.tar.gz". They can be obtained from the Downloads section of the Basler website or from Basler's FTP server:
ftp://Pylon4Linux-ro:h50UZgkl@ftp.baslerweb.com If you use either of these packages, you will not need to install any additional libraries. You must simply unpack the package according to the README and INSTALL files included in the package and at least set the environment variables appropriately, for example:
#(for 32 bit Linux)
export PYLON_ROOT=/opt/pylon export GENICAM_ROOT_V2_1=${PYLON_ROOT}/genicam export LD_LIBRARY_PATH=${PYLON_ROOT}/lib: ${GENICAM_ROOT_V2_1}/bin/Linux32_i86:$LD_LIBRARY_PATH For more details, refer to the README and INSTALL files included in the package. |
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| What are color filters? Color Filters for Single-Sensor Color Cameras
In general single-sensor color cameras use a monochrome sensor with a color filter pattern. Another way to achieve a color image with only one sensor would be to use a revolving filter wheel in front of a monochrome sensor, but this method has its limitations.
With the color filter pattern method of color imaging, no object point is projected on more than one sensor pixel, that is, only one measurement (for a single color or sum of a set of colors) can be made for each object point.
There are several different filter methods for generating a color image from a monochrome sensor. In the following some frequently used filter arrangements are detailed.
Bayer Color Filter (Primary Color Mosaic Filter)
The following table 1 shows the filter pattern for a sensor of size xs x ys (xs and ys being multiples of 2):
Complementary Color Mosaic Filter
The following table 2 shows the filter pattern for a sensor of size xs x ys (xs and ys being multiples of 2):
This is basically the same arrangement as the Bayer filter pattern, but instead of using primary colors (R, G, B) it works with complementary colors (magenta, cyan, yellow). The reason for this is that a primary color filter blocks of 2/3 of the spectrum (i.e. green and blue for a red filter) while a complementary filter blocks only 1/3 of the spectrum (i.e. blue for a yellow filter). Thus, the sensor is 2 times more sensitive. The tradeoff is a somewhat more complicated computation of the R, G, B values, requiring the input of each complementary color.
Primary Color Vertical Stripe Filter
Table 3 shows the filter pattern for a sensor of size xs x ys (xs being a multiple of 4):
![]() This arrangement is very simple and basically well suited to machine vision applications. The drawback is that the horizontal resolution is only 1/3 of the vertical resolution. |
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| What is a Signal-to-Noise Ratio and how can I improve it? Signal-to-Noise Ratio
An ideal camera sensor would convert a known amount of light into an exactly predictable output voltage. Unfortunately, ideal sensors (like all other electronic devices) do not exist. Due to temperature conditions, electronic interference, etc., sensors will not convert light 100% precisely. Sometimes, the output voltage will be a bit bigger than expected and sometimes, it will be a bit smaller. The difference between the ideal signal that you expect and the real-world signal that you actually see is usually called noise. The relationship between signal and noise is called the signal-to-nose ratio (SNR).
Signal-to-noise ratio is commonly expressed as a factor such as 20 to 1, 30 to 1, etc. Signal-to-noise ratio is also frequently stated in decibels (dB). The formula for calculating a signal-to-noise ratio in dB is: SNR = 20 x log (Signal/Noise). Once noise has become part of a signal, it can't be filtered or reduced. So it is a good idea to take precautions to reduce noise generation such as:
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| Can you tell me which network adapters are compatible with the Basler pylon performance driver? Basler provides two GigE Vision network drivers for interfacing Basler GigE Vision cameras:
To take advantage of the benefits of the Basler performance driver, we recommend using Intel Pro 1000 network adapters. These adapters generally work well with the performance driver. However, since the Intel Pro 1000 series has changed over the time, it may happen that the Basler performance driver does not support your particular Intel Pro 1000 adapter. To make sure that the Pro 1000 network adapter you are using is compatible, consult the table below that lists the currently supported Intel Pro 1000 chipsets and their corresponding Hardware IDs. Note that some chipsets are compatible with pylon version 2.1 or 2.2, but not with version 2.0. In the following table: Yes = is compatible Yes/M = is compatible but requires manual installation No = is not compatible * This device can also have "82541PI" markings. ** pylon operation with this chipset is unreliable. *** These devices can also have "82571GB" or "82572GI" markings (instead of "82571EB" or "82572EI"). The 82571GB and 82572GI devices are only used on Intel network interface adapters. The 82571GB is functionally equivalent to the 82571EB and the 82572GI is functionally equivalent to the 82572EI. † The Intel Gigabit CT Desktop Adapter uses this chipset, but this adapter does not work well with the performance driver. We recommend that you use Intel Pro 1000 series adapters. To check the Hardware IDs for your network adapter: 1. Click Start > Run. 2. Type in: devmgmt.msc 3. Click the OK button. The device manager will start. 4. Expand the node for Network Adapters. ![]() 5. Right click on the name of your Intel Pro 1000 adapter and select Properties from the drop down menu. 6. Click the Details tab and make sure that Hardware IDs is selected in the drop down list. ![]() Check the hardware IDs in the list on the Detail Tab against the table that appears earlier in this FAQ. If hardware IDs for your adapter do not match an ID in the table, you must use the Basler filter driver with your network adapter. Customers who happen to acquire an unsupported Intel Pro 1000 network adapter, but who still need to use the Basler performance driver, can contact the Basler support team. The support team will arrange shipment of the non-compatible network adapter to Basler AG and will attempt to get the adapter supported either by creating a hotfix for the performance driver or by including the adapter in the next Basler performance driver release. February 2012 |
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| What is PRNU? PRNU
When a fixed, uniform amount of light falls on the sensor cells in a digital camera, each cell in the camera should output exactly the same voltage. However, due to a variety of factors including small variations in cell size and substrate material, this is not actually true. When a uniform light is shined in the cells in a digital camera, the cells output slightly different voltages. This difference in response to a uniform light source is referred to as "Photo Response Non-Uniformity" or PRNU for short. Since PRNU is caused by the physical properties of the sensor itself, it is almost impossible to eliminate. PRNU is usually considered to be a normal characteristic of the sensor array used in a camera.One easy way to deal with PRNU is to use a look up table (LUT). With this method, the sensor cells in a camera are exposed to uniform light and an adjustment factor that would result in a uniform output is calculated for each sensor cell. The adjustment factor for each cell is stored in a table. When an image is captured, a software routine looks in the table and applies the appropriate correction factor to the output from each cell. PRNU can be made worse if the gain on your camera is set too low or if your exposure time is set too high (usually > 500 ms). |
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