Analysis of Color Constancy Methods for Recovering Skin Color Independent of Illuminants

Lee, Woo-Ram; Hwang, Dong-Hwan; Jun, Byoung-Min

doi:10.7840/kics.2011.36c.10.621

Cited by 3 publications

(3 citation statements)

References 1 publication

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“…Since D is outside A, the skin detection rate would be significantly deteriorated if the Gaussian model is not transformed. Hence, we translate A to C using equation (4). The color set of the skin sample will again be contained in the Gaussian model and the detection rate can be recovered.…”

Section: Rationale Of the Skin Color Model Adaptationmentioning

confidence: 99%

“…To overcome this problem, some researchers proposed to perform color constancy to adjust the input images prior to the skin segmentation process. 4 Other researchers designed mixture skin models to accommodate the varying lighting condition. 3,5 The success of the color constancy-based methods depends on two key factors: an accurate estimation of the light source color and an effective skin model which can produce decent skin classification results under the canonical lighting condition.…”

Section: Introductionmentioning

confidence: 99%

“…Otherwise, the skin detection procedure will not be successful. 4 Furthermore, the computational costs constitute another problem. The color constancy process must be conducted for each image frame, and thus, the accumulative computing costs become expensive.…”

Section: Introductionmentioning

confidence: 99%

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Skin color model adaptation under varying lighting conditions

Ueng

Chang

2016

Advances in Mechanical Engineering

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Skin region detection is crucial for face recognition, hand tracking, and motion detection. In the detection process, a skin color model is usually required to confine the distribution of skin colors. However, skin color models are sensitive to lighting conditions. Skin segmentation under varying lighting conditions produces poor results. This article presents a skin detection procedure for human-computer interaction sessions under varying lighting conditions. The proposed method requests a skin sample from the user to estimate the color temperature of the light source. Then, the color temperature is used to correct the skin sample. At the subsequent step, the mean of the corrected skin sample is utilized to adapt the skin color model. Finally, the adapted skin color model is employed to segment skin regions in the video stream. Tests using the proposed method and some adaptive skin detection algorithms have been conducted. Statistical data show that the proposed method is superior to color constancy methods and the Gaussian mixture model in skin region segmentation. The proposed method improves the true positive rate by more than 13% in segmenting skin regions of a database. Its true positive rate is 20% better if real-life images are used as test data.

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Section: Rationale Of the Skin Color Model Adaptationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Skin color model adaptation under varying lighting conditions

Ueng

Chang

2016

Advances in Mechanical Engineering

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An improved skin color model

Ueng

Chang

2016

2016 International Conference on Applied System Innovation (ICASI)

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Enhancement of Faded Images Using Integrated Compensation Coefficients Based on Multi-Scale Gray World Algorithm

Kyung

Kim

2014

The Journal of Korea Information and Communications Society

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Key Words : faded image enhancement, gray world algorithm, multi-scale process ABSTRACT Fading effect of old pictures and printings is shown up differently according to the ink property, temperature, humidity, illuminants, and so on. Faded image enhancement techniques based on illuminant estimation are proposed such as the gray world algorithm and white patch retinex methods. However, conventional simple operators are not suitable for enhancing faded images because partial fading effect is appeared differently. Thus, this paper presents a color enhancement algorithm based on integrating correction coefficients for faded images.First, the proposed method adopts local process by using multi-scale average mask. The coefficients for each multi-scale average mask are obtained to apply the gray world algorithm. Then, integrating the coefficients with weights is performed to calculate correction ratio for red and blue channels in the gray world assumption.Finally, the enhanced image is obtained by applying the integrated coefficients to the gray world algorithm. In the experimental results, the proposed method reproduces better colors for both wholly and partially faded images compared with the previous methods.

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Analysis of Color Constancy Methods for Recovering Skin Color Independent of Illuminants

Cited by 3 publications

References 1 publication

Skin color model adaptation under varying lighting conditions

Skin color model adaptation under varying lighting conditions

An improved skin color model

Enhancement of Faded Images Using Integrated Compensation Coefficients Based on Multi-Scale Gray World Algorithm

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