Effect of color illumination on color contrast in color vision application

Zhu, Zhaoda; Qu, Xinghua; Liang, Hai-Yu; Guanghui, Jia

doi:10.1117/12.869924

Cited by 8 publications

(5 citation statements)

References 5 publications

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“…Several researchers have tried to enhance texture visibility by shaping the spectral power distribution of the illuminant after having analysed the reflectance difference between two regions of interest. 9,10 Building further on this idea, Lee et al . 11 proposed an algorithm to find the optimal spectral distribution of the illuminant, making colour differences in the visual field as large as possible.…”

Section: Introductionmentioning

confidence: 99%

Optimising the illumination spectrum for tissue texture visibility

Wang

Cuijpers

Vogels

et al. 2017

Lighting Research & Technology

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A light-emitting diode based spectrum optimisation is proposed to enhance the visibility of the texture of biological tissue. This optimisation method is based on maximising perceptual colour differences between pairs of colour patches using images of biological tissue. This approach has two advantages. First, by weighting the importance of colour differences, the impact of glint or specular reflection is reduced automatically. Second, this optimisation method puts the priority on small colour differences which could be more useful in enhancing the visibility of tissue texture. Furthermore, a psychophysical experiment has been conducted to evaluate the effectiveness of the proposed method. To be able to generalise our conclusions, different biological tissue types are used. The results show that illumination spectra that are optimised based on human perceptual colour differences significantly improve the visibility of tissue texture compared to illuminants such as CIE D65, and white LED light.

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Section: Introductionmentioning

confidence: 99%

Optimising the illumination spectrum for tissue texture visibility

Wang

Cuijpers

Vogels

et al. 2017

Lighting Research & Technology

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“…For each coloured character, an appropriate LED illumination was selected to maximise the discriminability, which was more suitable than D65 illumination. 10 Vriesenga et al. have described how to design colour illumination to improve the discriminability of objects in colour images.…”

Section: Introductionmentioning

confidence: 99%

Optimising the illumination spectrum for enhancing tissue visualisation

Shen

Chang

Wang

et al. 2017

Lighting Research & Technology

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In operations, light reflected from biological tissue can be used for disease detection. In this paper, we used a visual entropy evaluation method to design the optimal illuminant to improve colour discriminability of biological tissue. The optimal spectral power distribution of the illuminant was obtained by maximising the visual entropy value of sample tissue based on the human visual system. In the experiment, multispectral imaging was used to measure the spectral reflectance of the tissue and colour clustering was conducted to extract its colour features. To verify the effectiveness of this method, simulated tissue images under illuminations with optimised spectral power distributions were compared with those under other light sources such as the standard illuminant D65 and white LED light sources. Results show that the sample under optimised illumination has a higher visual entropy value with better perceptual visibility.

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“…In our previous work, colorized vision system with the digital sensor and optimal LED array illuminator was investigated for color vision [9][10][11]. Nevertheless, the uncertainty of LED array illuminator for color measurement would be a deadly factor due to the stray light errors, the instabilities of colorimetric system, and the spectral mismatch of illumination.…”

Section: Introductionmentioning

confidence: 99%

Color Calibration for Colorized Vision System with Digital Sensor and LED Array Illuminator

Zhu

Song

Luo

et al. 2016

Active and Passive Electronic Components

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Color measurement by the colorized vision system is a superior method to achieve the evaluation of color objectively and continuously. However, the accuracy of color measurement is influenced by the spectral responses of digital sensor and the spectral mismatch of illumination. In this paper, two-color vision system illuminated by digital sensor and LED array, respectively, is presented. The Polynomial-Based Regression method is applied to solve the problem of color calibration in the sRGB andCIE L⁎a⁎b⁎color spaces. By mapping the tristimulus values from RGB to sRGB color space, color difference between the estimated values and the reference values is less than3ΔE. Additionally, the mapping matrixΦRGB→sRGBhas proved a better performance in reducing the color difference, and it is introduced subsequently into the colorized vision system proposed for a better color measurement. Necessarily, the printed matter of clothes and the colored ceramic tile are chosen as the application experiment samples of our colorized vision system. As shown in the experimental data, the average color difference of images is less than6ΔE. It indicates that a better performance of color measurement is obtained via the colorized vision system proposed.

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Effect of color illumination on color contrast in color vision application

Cited by 8 publications

References 5 publications

Optimising the illumination spectrum for tissue texture visibility

Optimising the illumination spectrum for tissue texture visibility

Optimising the illumination spectrum for enhancing tissue visualisation

Color Calibration for Colorized Vision System with Digital Sensor and LED Array Illuminator

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