Starfruit classification based on linear hue computation

In this paper, a classification process to group starfruit into six maturity indices is proposed based on 1- dimensional color feature called hue, which is extracted from the starfruit image. As the original hue is quantified from the nonlinear transformation of the 3-dimensional Red, Green and Blue color, this paper proposes a linear hue transformation computation based on the 2 colors of Red and Green. The proposed hue computation leads to a reduced computational burden, less computational complexity and better class discriminant capability. The hue is then applied as the input for the maturity classification process. The classification process is based on the hypothesis that for each of the maturity index, certain area of the starfruit surface is supposed to have distinctive value of the hue. In this work, the said starfruit surface area is set as 70% of the total area and based on 600 samples, the proposed technique results in 93% classification accuracy

Texture Segregation in Chromatic Element-Arrangement Patterns

We compare the perceived segregation of element-arrangement patterns1 which are composed of two types of squanes arranged in vertical stripes in the top and bottom regions and in a checkerboard in the middle region. The squares in a pattern are either equal in luminance and differing in hue or equal in hue and differing in luminance. Perceived segregation of squares differing in hue is not predicted by their rated similarity, but rather by the square-root of the sum of the squares of the differences in the outputs of the L-M and L+M-S opponent channels. Adaptation to the background luminance affects judgements of perceived segregation but does not affect judgments of perceived similarity. For a given background luminance, perceived segregation is a linear function of cone contrasts. Perceived hue similarity is instead a linear function of cone excitations across the background luminances. High and low luminance backgrounds decrease the perceived segregation of patterns differing in luminance. A high luminance achromatic background decreases the perceived segregation of patterns differing in hue but a low luminance achromatic background does not. The results indicate that the adaptation luminance affects the contribution of luminance differences between the two types of squares to perceived segregation but not the contribution of hue differences. For element-arrangement patterns composed of squares of equal luminance that differ in hue, perceived segregation is associated with differences in the perceived brightness of the hues. The results are consistent with the findings that the perceived segregation in element-arrangement patterns is primarily a function of the early visual mechanisms that encode pattern differences prior to the specification of the forms of the squares and their properties.Office of Naval Research (N00014-91-J-4100, N00014-94-1-0597, N00014-95-1-0409); Advanced Research Projects Agency (N00014-92-J-4015); Air Force Office of Scientific Research (F49620-92-J-0334); National Science Foundation (IIU-94-01659

A Display Calibration Technique based on Invariant Human Colour Mechanisms

When human observers are asked to adjust a coloured light such that it appears neither red nor green, or such that it appears neither yellow nor blue, most colour-normal observers have no difficulty in making these adjustments. These hue judgements are not significantly influenced by language or age [Saunders and van Brakel 1997] and individual differences in colour sensitivity are not reflected in the unique-hue settings [Webster et al. 2000]. The human colour system seems to be able to calibrate itself so that there is a remarkable agreement across observers in relation to these unique-hue judgements. Here we show how we can use the invariance of these unique-hue judgements to develop a colour calibration technique for display devices, which eliminates the need for an external calibration standard or a measurement device

No difference in variability of unique hue selections and binary hue selections

If unique hues have special status in phenomenological experience as perceptually pure, it seems reasonable to assume that they are represented more precisely by the visual system than are other colors. Following the method of Malkoc et al. (J. Opt. Soc. Am. A22, 2154 [2005]), we gathered unique and binary hue selections from 50 subjects. For these subjects we repeated the measurements in two separate sessions, allowing us to measure test-retest reliabilities (0.52≤ρ≤0.78; p≪0.01). We quantified the within-individual variability for selections of each hue. Adjusting for the differences in variability intrinsic to different regions of chromaticity space, we compared the within-individual variability for unique hues to that for binary hues. Surprisingly, we found that selections of unique hues did not show consistently lower variability than selections of binary hues. We repeated hue measurements in a single session for an independent sample of 58 subjects, using a different relative scaling of the cardinal axes of MacLeod-Boynton chromaticity space. Again, we found no consistent difference in adjusted within-individual variability for selections of unique and binary hues. Our finding does not depend on the particular scaling chosen for the Y axis of MacLeod-Boynton chromaticity space