A new image calibration technique for colposcopic images

Li, Wenjing; Soto-Thompson, Marcelo; Xiong, Yizhi; Lange, Holger

doi:10.1117/12.650218

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…Данная матрица позволяет любую координату цвета (например, координату R) в корректируемом изображении рассчитать как линейную комбинацию цветовых координат опорного изображения. Матрица включает 9 или 12 коэффициентов, оценка которых выполняется c помощью итерационного метода наименьших квадратов [16]- [18].…”

Section: панорамное изображениеunclassified

Endoscopic Images Digital Processing for Clinical Decision Support Systems

Obukhova

Motyko

Pozdeev

2019

Izv. vysš. učebn. zaved. Ross., Radioèlektron.

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The purpose of this research is to create new automatic methods for endoscopic image digital processing, ensuring their high ergonomics and the possibility of effective use in clinical decision support systems. As the result of investigation, the following methods were proposed: the detection and removal of specular highlights; compensation of radial and tangential geometric distortions; the mosaic panorama creation from the input video stream with low level of detail; brightness and contrast enhancement, providing simultaneous successful correction of both dark and bright areas of the image (uneven contrast) without significant underlining of the noise component typical for the existing nonlinear contrasting methods, especially in low-detail image areas; custom color correction based on linear transformation matrix taking into account endoscopic image characteristics and making it possible to customize color palette according to the physician individual preferences. The methods considered were successfully tested on real endoscopic images at the department of innovative medical devices of the Korean Electrotechnological Research Institute. The test results demonstrate their effectiveness and applicability in clinical decision support systems.

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Section: панорамное изображениеunclassified

Endoscopic Images Digital Processing for Clinical Decision Support Systems

Obukhova

Motyko

Pozdeev

2019

Izv. vysš. učebn. zaved. Ross., Radioèlektron.

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“…Besides, the calibrations performed are camera specific and may not be applicable for different cameras used under different conditions. Li et al (2006) developed a specific colour adjustment system to obtain close to true colour representations of colposcopic images used in auto diagnosis of cervical cancer and also in telemedicine related applications. Since the diagnosis is primarily based on the colour of the tissue observed under artificial light sources, they have found that variations in the light source provided different colours in the digital image acquired, which may obstruct reaching a clear and fast diagnosis.…”

Section: ‫يف‬ ‫ـي‬ ‫ـ‬ ‫قياس‬ ‫ـوء‬ ‫ـ‬ ‫ض‬ ‫ـدر‬ ‫ـ‬ ‫مص‬ ‫إىل‬ ‫ـة‬mentioning

confidence: 99%

In-situ colour correction for digital images acquired under non-standard lighting conditions

Manickavasagan

Alahakoon

2018

Jour. Agri. & Mar. Scie.

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Computer vision techniques using colour images are becoming popular in food and agriculture sector. Need of a standard illumination source is an important criterion in this approach to determine various attributes based on RGB values of the objects. In general, under laboratory conditions with standard lighting, an imaging system performs with high consistency in digitizing colour. However, in field conditions where the availability of a standard light source cannot be guaranteed, the colour interpretations may not yield accurate results. The objective of this study was to develop a simple algorithm to compensate for the variations in RGB values due to varying light conditions. It is intended to be useful in situations where taking digital images of objects without standard light sources is essential for a particular purpose. A set of quadratic transformation algorithms were developed to transform the RGB values of the images acquired under five different lighting conditions. The mean variance in RGB values of the image of a colour palette (with 6 different colours) taken under five lighting conditions were in the range of 277 – 548. After implementing the developed algorithm, this was reduced to 34 – 142. Similarly, this variance was reduced from 180 – 294 to 63 – 128 in the test conducted with a plant material. This algorithm can be easily adopted in all computer vision applications where variations in colour interpretations due to nonstandard lighting sources are common.

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Automatic image quality assessment for uterine cervical imagery

Gu¹,

Li²

2006

SPIE Proceedings

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A new image calibration technique for colposcopic images

Cited by 3 publications

References 10 publications

Endoscopic Images Digital Processing for Clinical Decision Support Systems

Endoscopic Images Digital Processing for Clinical Decision Support Systems

In-situ colour correction for digital images acquired under non-standard lighting conditions

Automatic image quality assessment for uterine cervical imagery

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