29.08.2014 • WhitepaperCameraCamera TestConvision CC-8171

Camera test: Samsung SNV-7080-P

In cooperation with Seetec, GIT SECURITY tests current and new video cameras under standardised conditions in the test laboratory of the SeeTec Hardware Competence Centre. The Ha...

Camera test: Samsung SNV-7080-P

In cooperation with Seetec, GIT SECURITY tests current and new video cameras under standardised conditions in the test laboratory of the SeeTec Hardware Competence Centre. The Hardware Competence Centre was set up because the data and performance specifications of network cameras as stated by manufacturers are often measured under different conditions and are not always reliable in practice. The results provided a sound basis for planning IP video projects and help to avoid unpleasant surprises. For the testing procedure, video ­sequences are produced under defined lighting scenarios and are then evaluated. Here, movements in the picture as well as night and backlight situations are taken into consideration.

The SNV-7080P is a dome camera from Samsung's 3 Megapixel camera series that is fitted with a 1/3" CMOS sensor and the new Samsung WiseNet2 DSP chipset. The camera has an internal SD/SDHC card slot and a motorized vario-focal lens. The picture can be transmitted in various levels of resolution from CIF (320 x 240) through 16:9 1080p Full HD format up to full 3 megapixels (2048 x 1536) that can be sent simultaneously, which enables the most important data stream to be sent to the display or the recorder. The SNV-7080 P supports H.264 and JPEG codecs.

Conclusion
As a 3 megapixel Full HD network camera the Samsung SNV 7080-P is impressive above all in its sharpness. No matter what the conditions, the camera delivers a sharp picture. There is already a slight image noise to be seen at 100 Lux that tends to increase as the light reduces, but this plays only a small role under such conditions. With a maximum transmission rate of 30 images/sec. the camera impresses with good motion clarity. In addition it has camera-based movement detection and video analysis functions such as face recognition, for example.

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