scholarly journals Bayesian approach to color-difference models based on threshold and constant-stimuli methods

2015 ◽  
Vol 23 (12) ◽  
pp. 15290 ◽  
Author(s):  
Fernando Brusola ◽  
Ignacio Tortajada ◽  
Ismael Lengua ◽  
Begoña Jordá ◽  
Guillermo Peris
Keyword(s):  
Bayesian Approach ◽  
Color Difference

scholarly journals A Bayesian approach for developing threshold color-difference models by the strip-pair comparison method

2021 ◽  
Author(s):  
Fernando Brusola ◽  
Ignacio Montañana ◽  
Begoña Albiñana ◽  
Jimena González-Del-Río ◽  
Ismael Lengua
Keyword(s):  
Bayesian Approach ◽  
Color Difference ◽  
Comparison Method ◽  
Pair Comparison

Modification of optical properties of PC-PBT/Cr2O3 and PC-PBT/CdS nanocomposites by gamma irradiation

2020 ◽  
Vol 92 (2) ◽  
pp. 20402
Author(s):  
Kaoutar Benthami ◽  
Mai ME. Barakat ◽  
Samir A. Nouh
Keyword(s):  
Refractive Index ◽  
Optical Properties ◽  
Band Gap ◽  
Color Difference ◽  
Band Gap Energy ◽  
Polybutylene Terephthalate ◽  
Γ Irradiation ◽  
Gap Energy ◽  
Vis Spectroscopy ◽  
Oxygen Atoms

Nanocomposite (NCP) films of polycarbonate-polybutylene terephthalate (PC-PBT) blend as a host material to Cr2O3 and CdS nanoparticles (NPs) were fabricated by both thermolysis and casting techniques. Samples from the PC-PBT/Cr2O3 and PC-PBT/CdS NCPs were irradiated using different doses (20–110 kGy) of γ radiation. The induced modifications in the optical properties of the γ irradiated NCPs have been studied as a function of γ dose using UV Vis spectroscopy and CIE color difference method. Optical dielectric loss and Tauc's model were used to estimate the optical band gaps of the NCP films and to identify the types of electronic transition. The value of optical band gap energy of PC-PBT/Cr2O3 NCP was reduced from 3.23 to 3.06 upon γ irradiation up to 110 kGy, while it decreased from 4.26 to 4.14 eV for PC-PBT/CdS NCP, indicating the growth of disordered phase in both NCPs. This was accompanied by a rise in the refractive index for both the PC-PBT/Cr2O3 and PC-PBT/CdS NCP films, leading to an enhancement in their isotropic nature. The Cr2O3 NPs were found to be more effective in changing the band gap energy and refractive index due to the presence of excess oxygen atoms that help with the oxygen atoms of the carbonyl group in increasing the chance of covalent bonds formation between the NPs and the PC-PBT blend. Moreover, the color intensity, ΔE has been computed; results show that both the two synthesized NCPs have a response to color alteration by γ irradiation, but the PC-PBT/Cr2O3 has a more response since the values of ΔE achieved a significant color difference >5 which is an acceptable match in commercial reproduction on printing presses. According to the resulting enhancement in the optical characteristics of the developed NCPs, they can be a suitable candidate as activate materials in optoelectronic devices, or shielding sheets for solar cells.

Exploring the Facial Color Representative Regions Using the Humanae Images

2020 ◽  
Author(s):  
Yuchun Yan ◽  
Hayan Choi ◽  
Hyeon-Jeong Suk
Keyword(s):  
Image Analysis ◽  
Future Study ◽  
Skin Color ◽  
Color Difference ◽  
Facial Skin ◽  
Female Images ◽  
Gender And Race ◽  
Facial Landmarks

It is difficult to describe facial skin color through a solid color as it varies from region to region. In this article, the authors utilized image analysis to identify the facial color representative region. A total of 1052 female images from Humanae project were selected as a solid color was generated for each image as their representative skin colors by the photographer. Using the open CV-based libraries, such as EOS of Surrey Face Models and DeepFace, 3448 facial landmarks together with gender and race information were detected. For an illustrative and intuitive analysis, they then re-defined 27 visually important sub-regions to cluster the landmarks. The 27 sub-region colors for each image were finally derived and recorded in L ∗ , a ∗ , and b ∗ . By estimating the color difference among representative color and 27 sub-regions, we discovered that sub-regions of below lips (low Labial) and central cheeks (upper Buccal) were the most representative regions across four major ethnicity groups. In future study, the methodology is expected to be applied for more image sources.

Verbal statistical learning: Prior knowledge impacts word identification but not metacognition

2020 ◽  
Author(s):  
Laetitia Zmuda ◽  
Charlotte Baey ◽  
Paolo Mairano ◽  
Anahita Basirat
Keyword(s):  
Task Performance ◽  
Prior Knowledge ◽  
Statistical Learning ◽  
Cognitive Processes ◽  
Bayesian Approach ◽  
Word Identification ◽  
Artificial Language ◽  
Artificial Languages ◽  
Transitional Probabilities ◽  
Fully Bayesian

It is well-known that individuals can identify novel words in a stream of an artificial language using statistical dependencies. While underlying computations are thought to be similar from one stream to another (e.g. transitional probabilities between syllables), performance are not similar. According to the “linguistic entrenchment” hypothesis, this would be due to the fact that individuals have some prior knowledge regarding co-occurrences of elements in speech which intervene during verbal statistical learning. The focus of previous studies was on task performance. The goal of the current study is to examine the extent to which prior knowledge impacts metacognition (i.e. ability to evaluate one’s own cognitive processes). Participants were exposed to two different artificial languages. Using a fully Bayesian approach, we estimated an unbiased measure of metacognitive efficiency and compared the two languages in terms of task performance and metacognition. While task performance was higher in one of the languages, the metacognitive efficiency was similar in both languages. In addition, a model assuming no correlation between the two languages better accounted for our results compared to a model where correlations were introduced. We discuss the implications of our findings regarding the computations which underlie the interaction between input and prior knowledge during verbal statistical learning.

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