Box identification and recognition is one of the most commonly cited tasks that need to be addressed in industry. The challenges posed here are that boxes varying in terms of colour and or/size may be dealt with simultaneously, and also have an adhesive label or recognition code. The spatial arrangement of the boxes also tends to be random. Arrangements can vary from a scenario involving completely different boxes to boxes positioned close to one another, or even just a solitary box.
Beside a camera with a suitable sensor, the optics as well as the lighting system are the fundamental pillars for good image qualities and for this reason for reliable applications. A flash ensures well-illuminated and sharp images. In order that an unchanging illumination is guaranteed over long periods, digital lighting controllers are used. The following white paper shows, how lighting systems improve the image quality.
Within the technical data of industrial cameras you will find the range of permissible ambient temperature. Ambient temperature is the temperature of the air around the device at a given distance. Typically the lower limit is set to zero degrees Celsius simply by the fact that we should avoid condensation both inside the camera and on the housing, as it is usually not protected against water ingress. The upper temperature limit is commonly a worst case limit with a margin to be on the safe side. There are further issues to consider – more in this white paper.
Industrial cameras in outdoor applications have to face several challenges: changing light conditions because of night and day, and if they are used in traffic, backlight will be a common problem. High dynamic sensors are the solution, but they are wrongly assumed to be expensive. The CMOS sensor AR0331 from Aptina/ON Semiconductor with HDR modes proves the contrary. The features and how you can work with the sensor will show the following white paper.
The following document describes the usage of the image averaging property which can be found in MATRIX-VISION cameras of the mvBlueFOX3 and mvBlueCOUGAR-X family. It requires camera firmware version 2.8.0 for the mvBlueFOX3-1 family and 2.14.2 or newer for the mvBlueFOX3-2 family. Its purpose is to improve image quality by temporal averaging of images. This is fundamentally different to image processing algorithms e.g. low pass filtering or mean filtering of single images which also lead to loss of details in an image.
The consumer interface USB 3.0 was introduced in 2010 and is very popular not only for the USB 2.0 backwards compatibility. The USB 3.0 interface supports a gross bandwidth of 5000 MBit/s, however, maximum cable length of 3.5 m (using consumer cables) is only supported (8 m is possible with good cables). But there are other ways to extend the length. This white paper provides an overview of aspects and other things about this issue.
Camera timestamps are a recommended GigE Vision/GenICam/SFNC feature to add the information when an image was taken (exactly: when the exposure of the image started). Without additional synchronization it is merely a camera individual timer with a vendor specific increment and implementation dependent accuracy. Each camera starts its own timestamp beginning with zero and there are no means to adjust or synchronize them among cameras or host PCs. There is effort ongoing to widely establish the precision timestamp according to IEEE 1588 into GigE Vision cameras. This involves cameras which are able to perform the required synchronization as well as specific network hardware and driver software and procedures to do and maintain the synchronization. There are many applications which do not or cannot profit from 1588 but have certain synchronization needs. The following article describes solutions for these scenarios.
Whereas machine vision applications usually use constant lighting, there has been a trend to use GigE Vision cameras due to long cable length also in outdoor applications such as traffic monitoring, security, or sports. This enforces the need for controlling the image brightness by means of automatic gain or auto exposure on the one hand but also have possibilities to adjust field of view or zoom, or focus, or iris.
Many application fields like digital printing industry or the human medicine require a natural display of colors. To illustrate the importance of color fidelity, you can think about a doctor using an endoscope during an operation who wants to remove the right tissue. The purpose of this white paper is to show how you can optimize the color fidelity of a camera, so that it looks as natural as possible on different displays and for human vision.