Cloud service for detection of human skin color

Srimaharaj, Wanus; Hemrungrote, Sirichai; Chaisricharoen, Roungsan

doi:10.1109/iscit.2015.7458294

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…The intensity of brown color was based on von Luschan's Chromatic Scale: a scale of 14 or less was negative, 15 or more to 19 was weak, 20 or more to 26 was moderate, and 27 or more was strong staining. [24] The degree of expression was indicated by summing the scores for each of intensity and continuity.…”

Section: Histopathologic Analysismentioning

confidence: 99%

The Impact of Enteral Nimodipine on Endothelial Cell Apoptosis in an Animal Subarachnoid Hemorrhage Model

Cho,

Byoun,

Park

et al. 2024

Neurocrit Care

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Objective: Enteral nimodipine is the most evidence-based and widely used drug for the treatment of delayed cerebral ischemia (DCI) and is known to have various neuroprotective functions. However, the neuroprotective mechanism of nimodipine still remains unclear and the effects of nimodipine remain ambiguous. Herein, we studied the effect of enteral nimodipine on endothelial apoptosis after subarachnoid hemorrhage (SAH).Method: SAH was experimentally introduced in white rabbits (n=42) that were grouped: enteral nimodipine (group N, n=14); a control that received normal saline (group S, n=13); and a control without hemorrhage (group C, n=15). On the third day after SAH induction, the brain stem, including the vertebrobasilar vascular system, was extracted. The effects of enteral nimodipine were analyzed by group using histopathologic analysis, including immunohistochemical staining of apoptosis-related proteins (Bcl2 [anti-apoptotic] and Bax [pro-apoptotic]).Result: Cytoplasmic vacuolation of smooth muscle cells was observed in groups S and N, and was more prominent in group S. Endothelial desquamation was observed only in group S. For the basilar artery, expression of Bcl2 and Bax in group N was lower than in group S, but signi cant differences were not observed (p = 0.310 and p = 0.710, respectively). In penetrated arterioles, the expression of Bax in group N was signi cantly lower than that of group S (p < 0.001). The thickness of the tunica media in the basilar artery was thinner in group N than in group S (p < 0.001). Conclusion:This study suggests that enteral nimodipine may have a neuroprotective function by inhibiting endothelial apoptosis in small arterioles and preventing smooth muscle cell proliferation in large arteries.

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Section: Histopathologic Analysismentioning

confidence: 99%

The Impact of Enteral Nimodipine on Endothelial Cell Apoptosis in an Animal Subarachnoid Hemorrhage Model

Cho,

Byoun,

Park

et al. 2024

Neurocrit Care

View full text Add to dashboard Cite

show abstract

“…According to the findings of the research [10], color detection may also be accomplished with the help of mechanisms that have been adjusted to a diverse range of color space directions and that have wide and linear spectrum sensitivities. The first reports of the previous work [11] were based on color pictures that were felt and duplicated using tri-stimulus values with spectral composition that was carefully adjusted in line with the principles of color science [12]. [11] These color images were also recreated.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The first reports of the previous work [11] were based on color pictures that were felt and duplicated using tri-stimulus values with spectral composition that was carefully adjusted in line with the principles of color science [12]. [11] These color images were also recreated. [12] When determining an area's saturation, the color richness of that region is compared to the brightness component of that region.…”

Section: Literature Reviewmentioning

confidence: 99%

Application access for chromatic color detection

Umarani,

Dimpusowjanya,

Poojitha

et al. 2023

J. Phys.: Conf. Ser.

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The process of identifying specific examples of an item inside an image or video is referred to as “object detection,” and it is one of the computer vision techniques. When individuals look at pictures or movies, they are able to recognize and find things that are of interest to them. The primary goal of the field of object recognition is to achieve this level of intelligence via the use of a computer. Image segmentation and blob analysis, which uses simple object properties such as size, shape, or color, and Feature-based object detection, which uses feature extraction, matching, and RANSAC to estimate the location of an object, are two of the many common techniques that are used in conjunction with deep learning and machine learning-based object detection. There are also many other common techniques that are used in conjunction with deep learning and machine learning-based object detection. The most challenging aspects of object detection are the processes of categorizing things and pinpointing their locations. When seen from a different perspective, the same object might seem to be completely different. Detection algorithms have a tough time distinguishing between various things at different scales and perspectives since the sizes and proportions of items almost always alter. The camera input would be used to determine an object’s shape, according to this project’s proposal. Circle, square, and triangle are the three distinct shapes that we are determining an item to be right now. The finished result is shown in MATLAB’s graphical user interface (GUI). The productive identification process is carried out with the assistance of MATLAB. Using the SFTA Algorithm, the application extracts features from the specific image of a video. The neural network algorithm is used to classify the image of video. Image segmentation and image detection are two examples of related computer vision methods that are inextricably intertwined with object recognition. These techniques allow us to better comprehend and analyze the situations shown in movies and still photographs. It has been determined whether or not the suggested system is suitable. Because of this, the testing has shown that the suggested system generates generally accurate indications of real performance at a rate of 99.4%.

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Hyperspectral Imaging Database of Human Facial Skin

Gomes,

Nascimento,

Linhares

2024

Appl Spectrosc

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The perceived color of human skin is the result of the interaction of environmental lighting with the skin. Only by resorting to human skin spectral reflectance, it is possible to obtain physical outcomes of this interaction. The purpose of this work was to provide a cured and validated database of hyperspectral images of human faces, useful for several applications, such as psychophysics-based research, object recognition, and material modeling. The hyperspectral imaging data from 29 human faces with different skin tones and sexes, under constant lighting and controlled movements, were described and characterized. Each hyperspectral image, which comprised spectral reflectance of the whole face from 400 to 720 nm in 10 nm steps at each pixel, was analyzed between and within nine facial positions located at different areas of the face. Simultaneously, spectral measurements at the same nine facial positions using conventional local point and/or contact devices were used to ascertain the data. It was found that the spectral reflectance profile changed between skin tones, subjects, and facial locations. Important local variations of the spectral reflectance profile showed that extra care is needed when considering average values from conventional devices at the same area of measurement.

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Cloud service for detection of human skin color

Cited by 6 publications

References 11 publications

The Impact of Enteral Nimodipine on Endothelial Cell Apoptosis in an Animal Subarachnoid Hemorrhage Model

The Impact of Enteral Nimodipine on Endothelial Cell Apoptosis in an Animal Subarachnoid Hemorrhage Model

Application access for chromatic color detection

Hyperspectral Imaging Database of Human Facial Skin

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