By Linh Viet Tran
Read Online or Download Efficient Image Retrieval With Statistical Color Descriptors PDF
Similar nonfiction_3 books
Rethinking development offers a hard reevaluation of 1 of the an important principles of Western civilization; the inspiration of development. growth usually turns out to became self-defeating, generating ecological deserts, overpopulated towns, exhausted assets, decaying cultures, and frequent emotions of alienation.
This terribly transparent exposition at the knowledge part of the advisor to the Bodhisattva's lifestyle is predicated on an oral educating given in India by way of His Holiness the Dalai Lama ahead of an viewers of hundreds of thousands of Tibetans and Westerners in 1979. Shantideva's consultant to the Bodhisattva's lifestyle is likely one of the most vital texts within the Mahayana culture of Buddhist perform.
- Microbial Pathogenomics (Genome Dynamics)
- Self-Therapy for the Stutterer
- Selected works. Vol.3
Additional info for Efficient Image Retrieval With Statistical Color Descriptors
22 Fundamentals on Color used in Cathode Ray Tube (CRT) monitors, television, scanners, and digital cameras. For a monitor the phosphor luminescence consists of additive primaries and we can simply parameterize all colors via the coeﬃcients (α, β, γ), such that C = αR + βG + γB. The coeﬃcients range from zero (no luminescence) to one (full phosphor output). In this parametrization the color coordinates ﬁll a cubical volume with vertices black, the three primaries (red, green, blue), the three secondary mixes (cyan, magenta, yellow), and white as in Fig.
The histogram is the simplest tool. Other ways of describing color information in CBIR include the use of dominant colors, or color signatures, and color moments. Color histogram Statistically, a color histogram is a way to approximate the joint probability of the values of the three color channels. The most common form of the histogram is obtained by splitting the range of the data into equally sized bins. Then for each bin, the number of points from the data set (here the colors of the pixels in an image) that fall into each bin are counted and normalized to total points, which gives us the probability of a pixel falling into that bin.
In the CIE LAB color space, three components are used: L* is the luminance axis, a* and b* are respectively red/green and yellow/blue axes, see Fig. 11. Although CIE LAB provides a more uniform color space than previous models, it is still not perfect, see for example (Luo, 1999). 6) The constants Xn , Yn , and Zn are the XYZ values for the chosen reference white point. When working with color monitors good choices could be something close to D65’s XYZ coordinates. As CIE LAB, CIE LUV is another color space introduced by CIE in 1976.