February 6, 2014

              Innovation For ITS Applications: Network Cameras With Unique Real-time Trigger and Now With Uncompressed Images

              ITS News
              When it comes to picking a camera for their system, traffic customers are often faced with a flood of options. The primary options are IP cameras or industrial (machine vision) cameras. There are pros and cons to either choice (For more on this, see our White Paper on "Optimal Vision Ability by Cameras in Intelligent Traffic Systems"). Basler has now succeeded at integrating useful functions for traffic applications previously found in industrial cameras into their IP cameras. This includes on the one hand the real-time trigger function based around specific events to be recorded parallel to the video stream and, in a new development, to output them in the uncompressed YUV format. On the other hand, the BIP cameras with their high-sensitivity global shutter sensors produce top-quality images even for fast moving objects.

              Real-time trigger and YUV-Images – why are these important?

              One milestone involves the implementation of the real-time trigger function to record individual JPEG images of specific events such as traffic violations parallel to the video stream. Basler has expanded this trigger function to include yet another option: Basler IP cameras can now also produce uncompressed images (YUV feature) that deliver as much detail as possible. The images are sent directly to the PC in uncompressed form, involving a relatively large volume of data. The benefit is that no image information is lost in the compression process. Algorithms such as LPR (license plate recognition) produce significantly better results than for compressed images such as JPEG or even H.264.

              The first model with this YUV feature will be the BIP2-1600-25c-dn with its highly sensitive 2 MP sensor. This camera is the ideal choice for any type of license plate detection. It has already proven its value in a variety of security and enforcement applications, and is particular attractive in the LPR field for tasks like dragnet investigations.

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