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Vision CampusCamera Technology Interfaces and Standards Markets and Applications Vision Systems and ComponentsCamera TechnologyComparison between Sony's IMX CMOS sensor series Why should I color calibrate my camera? Expert Tips to Find the Right Lens for a Vision System Expert Tips for Embedded Vision Systems What Is Multispectral Imaging? Comparison of CMOS cameras Color in Image Processing Processing Boards in Embedded Vision What Is Image Processing 3D Technologies in Image Processing What Is Embedded Vision Why CMOS Image Sensors? What Is Time of Flight? What Is Image Quality? Camera Sizes How does a Digital Camera Work? CMOS vs. CCD: Sensor Technology Real-Time Capability NIR: Seeing Clearly Even in Low Light High-Sensitivity Industrial CamerasShow moreShow lessInterfaces and StandardsSystem Setup with CoaXPress 2.0 What Is CoaXPress? Which interface for Embedded Vision? Multi-Camera Systems with GigE 2.0 USB 3.0 – Interface of the Future Camera Link Gigabit Ethernet (GigE) GenICam Standard USB 3.0 and USB3 VisionMarkets and ApplicationsCameras for Fluorescence Microscopy What Is the Role of Computer Vision for Industry 4.0? What Is Deep Learning? Robots with Vision Technology Blockchain for IoT Sensor Producers How will IoT change retail? How Do Machines Learn? IoT Applications in the Smart City Benefits of Cameras in Medicine Lab Automation with Vision Medicine with Vision Image Processing in Industry 4.0 Machine Vision Automated Optical Inspection Color Calibration in Medical TechnologyShow moreShow lessVision Systems and ComponentsSoftware in Image Processing Image Pre-processing Strengthens and Streamlines Image Processing Systems How to Find the Right Lighting for Your Vision System? What is a Machine Vision SDK Lighting How Can I Find the Right Lens? Components of a Vision System Cutting Through the Noise: Camera Selection Image Processing Systems — The Basics
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What is the RGB color space?
Because the human eye only has color sensitive receptors for red, green and blue, it is theoretically possible to decompose every visible color into combinations of these three “primary colors.” Color monitors, for instance, can display millions of colors simply by mixing different intensities of red, green and blue. It is most common to place the range of intensity for each color on a scale from 0 to 255 (one byte). The range of intensity is also known as the “color depth”.
The possibilities for mixing the three primary colors together can be represented as a three dimensional coordinate plane with the values for R (red), G (green) and B (blue) on each axis. This coordinate plane yields a cube called the RGB color space:
If all three color channels have a value of zero, it means that no light is emitted and the resulting color is black (on a monitor, for example, it cannot be blacker than the surface of the monitor producing 0 light). If all three color channels are set to their maximum values (255 at a one byte color depth), the resulting color is white. This type of color mixing is also called “additive color mixing”:
If you draw a diagonal from the black (0, 0, 0) origin point of the color cube to the white (255, 255, 255) point, you will get a line where each point on the line has identical R,G and B values. The result of having the same value for all three color channels is the color gray. The only thing that changes as you move along this diagonal is the intensity of the shade of gray as you go from black to white.
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