Color to gray conversions in the context of stereo matching algorithms

Benedetti, Luca; Corsini, Massimiliano; Cignoni, Paolo; Callieri, Marco; Scopigno, Roberto

doi:10.1007/s00138-010-0304-x

Cited by 28 publications

(14 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As expected, the baselines of other coloured substrates were higher compared to the black substrate. This was because the grey scale algorithms used by the scanner converted the colour papers into a higher shades of grey depending on the original pixel values of the colour in RGB colour space [29]. Since the image analysis method used relies on the contrast between the deposited web area and the background, using a bright substrate paper limits the capability of the method as evidenced in Figure 9.…”

Section: Resultsmentioning

confidence: 99%

An investigation of using grey scale image analysis for predicting the amount of deposited electrospun nanofibres

Nurfaizey

Long

Daud

et al. 2019

JMES

View full text Add to dashboard Cite

When electrospinning, the amount of electrospun fibres deposited is difficult to determine due to the extremely small size and light weight of the fibres. Several methods have been used to predict the amount of deposited fibres including weighing, imaging and direct measurement. Yet, these methods have drawbacks that make them unsuitable for commercial scale process control. In this study, an image analysis method is used to predict the amount of deposited fibres over a significant area. When images of electrospun fibres are converted into grey scale images, it is suggested that the amount of fibres deposited can be predicted by measuring the grey scale intensity. Weighing method was used to validate the image analysis results. Weighing method was found wanting when the deposition time was short (p>0.05) due to the insignificant fibre masses compared to the variation of substrates. The results suggest that image analysis method could be used to predict the amount of deposited electrospun nanofibres. Test on different polymers and substrates showed that the method was still capable to distinguish the samples. The developed method has the potential to be applied as an in-line non-destructive quality control method for electrospun fibre manufacture.

show abstract

Section: Resultsmentioning

confidence: 99%

An investigation of using grey scale image analysis for predicting the amount of deposited electrospun nanofibres

Nurfaizey

Long

Daud

et al. 2019

JMES

View full text Add to dashboard Cite

show abstract

“…By default, MATLAB has a built in function that implements this conversion, taking ðc r ; c g ; c b Þ ¼ ð0:2989; 0:5870; 0:1140Þ. 14 Regardless of whether color is separated or combined into a single intensity value according to Eq. (11), we can now discuss how to obtain X L ðnÞ and Y L ðnÞ from a matrix of pixel intensities with M rows and N columns in which the same spatial information is encoded in each of the M rows, corresponding to Fig.…”

Section: Discussionmentioning

confidence: 99%

Measuring the spatial resolution of an optical system in an undergraduate optics laboratory

Leung

Donnelly

2017

American Journal of Physics

View full text Add to dashboard Cite

Two methods of quantifying the spatial resolution of a camera are described, performed, and compared, with the objective of designing an imaging-system experiment for students in an undergraduate optics laboratory. With the goal of characterizing the resolution of a typical digital single-lens reflex (DSLR) camera, we motivate, introduce, and show agreement between traditional test-target contrast measurements and the technique of using Fourier analysis to obtain the modulation transfer function (MTF). The advantages and drawbacks of each method are compared. Finally, we explore the rich optical physics at work in the camera system by calculating the MTF as a function of wavelength and f-number. For example, we find that the Canon 40D demonstrates better spatial resolution at short wavelengths, in accordance with scalar diffraction theory, but is not diffraction-limited, being significantly affected by spherical aberration. The experiment and data analysis routines described here can be built and written in an undergraduate optics lab setting.

show abstract

“…q R , q G , q B can be obtained using a color camera or color filters. The grey level of the color camera can be calculated by various methods (Bala and Eschbach 2004;Neumann, Adik, and Nemcsics 2007;Benedetti et al 2010). A monochrome camera detects the grey levels of intensity, I(x, y) which is related to q M .…”

Section: Optical Mixer and Rgb Control For Fine Images 215mentioning

confidence: 99%

An Optical Mixer and RGB Control for Fine Images using Grey Scale Distribution

Kim

Cho

2012

International Journal of Optomechatronics

View full text Add to dashboard Cite

We considered the issue of color mixing from the viewpoint of gray scale images and investigated the effect of the mixed light. The goal of this study was to improve the quality of the grey scale images by using mixed RGB illumination. The mixing mechanism and image quality were formulized and applied to a machine vision system with an RGB mixer. The RGB mixer was made of RGB LEDs, a power AMP, a mixing chamber, and a bundle of optical fibers. The intensity of the RGB light was adjusted by varying the 12 bit DAC voltage. The optical characteristics of the RGB LEDs were measured by a spectrometer. The color variation of the mixed light was monitored by a chromatic meter. Grey scale images were captured and analyzed under various lighting conditions provided by the mixer. The optimal illumination was determined by the distribution of the grey scale in the captured image. The chromatic diagram showed that various colors can be generated, and the image histogram showed that the mixed light can increase the quality of the grey scale image.

show abstract

Color to gray conversions in the context of stereo matching algorithms

Cited by 28 publications

References 29 publications

An investigation of using grey scale image analysis for predicting the amount of deposited electrospun nanofibres

An investigation of using grey scale image analysis for predicting the amount of deposited electrospun nanofibres

Measuring the spatial resolution of an optical system in an undergraduate optics laboratory

An Optical Mixer and RGB Control for Fine Images using Grey Scale Distribution

Contact Info

Product

Resources

About