MadSci Network: Engineering |
A standard color camera allows one to identify the various shades of color that most humans see. Typically, these cameras capture energy in the red, green and blue parts of the visible spectrum. There are parts outside of the camera's range, which is known as the gamut, that we can see, but are not captured by the camera. One example is the "neon" glow of neon colored paper, which is usually not well represented in digital images. Some standard color cameras see beyond our capabilities, particularly into the near-infrared. An example of this can be seen by aiming the camera at an infrared remote control while videoing the little emitter. You will see a red dot appear in the picture that you cannot see. Every color we see is determined by how our brain interprets these three colors. Often, when one wants to determine the color of something, we convert the RGB color image into a different "color space", known as IHS, which stands for Intensity, Hue, and Saturation. The I-part is basically what you might think of as the 'black and white" or grayscale part of the image. It is calculated for each pixel as the average of the R, G, and B values. The S-part is the amount of color present at a given pixel and it is often calculated as 1 - min(R,G,B)/I. The H-part represents the color of a given pixel, independent of how bright or how much color is present. It is sometimes calculated as [pi/2-arctan((2R-G-B)/sqrt(3)*(G-B))+pi]/2pi for G < B. There is another equation for when B < G. The H-part of the IHS color space is sometimes used in image processing to work with parts of an image independent of illumination and shadow, because the hue tends to remain similar whether or not the illumination changes. (The process I have described is similar to, although not exactly the same as, the process used for standard Color TV signals that also work on B&W TV equipment. Basically, the B&W TV only uses the I-part of the picture signal.) One must be a little careful when we talk about colors. The colors we, as humans, see is due to the detection of different bands of the spectrum by our "cone" cells in the retina. We have cones that are sensitive in the red, blue and green bands. While we can distinguish between subtle combinations of these broader bands, we cannot differentiate between light energy within a smaller portion of a band. So for instance, two different materials may emit or reflect light within the green band at slightly different wavelengths, but because we see only over a wide range of wavelengths, they both look similarly green to us. To solve this, some special cameras have been built that isolate much smaller parts of the spectrum. These cameras are known as hyperspectral (hundreds of bands) or ultraspectral (thousands of bands) cameras and allow one to distinguish between various materials based on subtle difference in their spectra. Your choice of camera will depend upon what you want to do. I hope that i have given you enough info to develop your own decision. I would say that for all but the most demanding applications, a standard color camera (still or video) will probably do what you want. You may have to convert the standard RGB output to the IHS space to get what you want, tho. Good luck, Todd Jamison Chief Scientist, Observera, Inc.
Try the links in the MadSci Library for more information on Engineering.