In this paper we aim to face with a more challenging and general problem: the analysis of line scratches in still images, regardless of their orientation, color, and shape.
The problem of processing scratches is much harder to deal in still images than in old movies, at least for two reasons: first, scratches in still images may have any possible orientation, color, and width while scratches in video have very specific features (see Figure 2); second, no temporal information can be used to process them.
That's true in terms of geographical point of origin, ethnic heritage, ability/disability, age, language, lifestyle preference, sexual orientation, color, size, and every other way of categorizing people.
Equality for everyone, regardless of race, gender, sexual orientation, color, or creed, goes against everything they stand for, so the fact that they are coming to protest me means that they realize a change is occuring.
Along with inviting him into our Glee writers room, I will also let him observe our casting process...so he can witness first hand--and speak to--actors who audition for our show and who are already series regulars--actors who are encouraged to read for ALL roles, no matter what their sexual orientation, color or gender.
The orientation – color interaction (F = 7.27, p = 0.007) was significant, showing that the orientation affected the letter detection probability for items sharing the target color only, suggesting the existence of grouping phenomena.
According to the relative contribution ratios, the selected feature types are edge orientation histogram, color coherence, color histogram, and SBN color.
The software outputs a stereonet of discontinuity orientations colored by joint set family, an image of the 3-dimensional model with each mapped discontinuity colored by the set family, and a text file of discontinuity orientations.
For early delays, the orientation-color interaction was not significant at all (F = .69, p = 0.52, see Fig. 10 B ., whereas it was significant for late delays (F = 26.72, p<0.0001, see Fig. 10 C).
Low-level vision features (orientation, brightness, color channels tuned to red, green, blue and yellow hues) are extracted from the original color image at several spatial scales (depending on the image size).
In video, we estimate head orientation from color information by exploiting spatial redundancy among cameras.
