• Journal of Broadcast Engineering
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• v.22 no.2
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• pp.207-213
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• 2017

In order to accurately perform multispectral imaging using a multiplexed illumination, intensity of illumination in a scene must be uniform. For image acquisition that requires accurate color information, even if not multispectral imaging, the illumination information must be accurate, and a flat light source or illumination calibration is performed for accurate illumination characteristics. In this paper, we propose a method of color correction to uniformly illuminate an image with non-uniform illumination intensity. The proposed method uses multispectral imaging instead of illumination calibration for color correction. First of all, we perform multispectral imaging with two images obtained from non-uniformity illumination to acquire spectral reflectance. The obtained reflection spectrum is relit as the illumination characteristic of the image obtained from general planar light such as fluorescent light or sunlight. By comparing the image obtained by relighting with the uniformly illuminated image, the non-uniformity of the illumination is confirmed, and the color correction is performed as the image obtained from the uniform image. It is expected that the experimental results will confirm whether the non-uniformity of the illumination is uniformly corrected and reduce the restriction of illumination in obtaining the color information of the image.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1926-1931
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• 2012

We investigated a novel fast non-uniform illumination correction method for bi-level images. The proposed method divides a bi-level image into sub-images and roughly estimates block-wise illumination by low pass filtered maximum values of sub-images. After that, we apply bilinear interpolation using the block-wise illumination to estimate non-uniform illumination, and compensate for the effect of non-uniform illumination using the estimated illumination. Since the proposed method is not based on computation intensive iterative optimization, the proposed method can be used effectively for applications that require fast correction of non-uniform illumination. In simulations, the proposed method showed more than 20 times faster speed than existing entropy minimization method. Moreover, in simulations and experiments, the restored images by the proposed method were more close to true images than images restored by conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.816-839
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• 2023

In a random vector functional link (RVFL) network, shortcomings such as local optimal stagnation and decreased convergence performance cause a reduction in the accuracy of illumination correction by only inputting the weights and biases of hidden neurons. In this study, we proposed an improved regularized random vector functional link (RRVFL) network algorithm with an optimized grey wolf optimizer (GWO). Herein, we first proposed the moth-flame optimization (MFO) algorithm to provide a set of excellent initial populations to improve the convergence rate of GWO. Thereafter, the MFO-GWO algorithm simultaneously optimized the input feature, input weight, hidden node and bias of RRVFL, thereby avoiding local optimal stagnation. Finally, the MFO-GWO-RRVFL algorithm was applied to ameliorate the performance of illumination correction of various test images. The experimental results revealed that the MFO-GWO-RRVFL algorithm was stable, compatible, and exhibited a fast convergence rate.

• Journal of the HCI Society of Korea
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• v.6 no.1
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• pp.21-26
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• 2011

This paper presents a robust method for facial image synthesis under varying illumination by combining illumination correction and Poisson image processing techniques. The presented method automatically detects skin area and corrects highly saturated regions that can cause bad effects on the final synthesis image. The developed method can be applied to various facial synthesis applications by correcting illumination variations that can occur frequently on photos taken with a camera phone.

• Journal of the Optical Society of Korea
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• v.6 no.4
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• pp.180-184
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• 2002

In this study, we investigated mask errors, photo errors with attenuated phase shift mask and off-axis illumination, and etch errors in dry etch conditions. We propose that total process proximity correction (TPPC), a concept merging every process step error correction, is essential in a lithography process when minimum critical dimension (CD) is smaller than the wavelength of radiation. A correction rule table was experimentally obtained applying TPPC concept. Process capability of controlling gate CD in DRAM fabrication should be improved by this method.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.114-123
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• 2014

Vehicle Black Box (Event Data Recorder EDR) only recognizes the general surrounding environments of load. In addition, general EDR is difficult to recognize the images of a sudden illumination change. It appears that the lens is being a severe distortion. Therefore, general EDR does not provide the clues of the circumstances of the accident. To solve this problem, we estimate the value of Normalized Luminance Descriptor(NLD) and Normalized Contrast Descriptor(NCD). Illumination change is corrected using Normalized Image Quality(NIQ). Second, we are corrected lens distortion using model of Field Of View(FOV) based on designed method of fisheye lens. As a result, we propose integration algorithm of two methods that correct distortions of images using each Gamma Correction and Lens Correction in parallel.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1470-1472
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• 2003

Hyperion, as hyperspectral data, is carried on NASA’s EO-1 satellite, can be used in more subtle discrimination on forest cover, with 224 band in 360 ?2580 nm (10nm interval). In this study, Hyperion image is used to investigate the effects of topography on the classification of forest cover, and to assess whether the topographic correction improves the discrimination of species units for practical forest mapping. A publicly available Digital Elevation Model (DEM), at a scale of 1:25,000, is used to model the radiance variation on forest, considering MSR(Mean Spectral Ratio) on antithesis aspects. Hyperion, as hyperspectral data, is corrected on a pixel-by-pixel basis to normalize the scene to a uniform solar illumination and viewing geometry. As a result, the approach on topographic effect normalization in hyperspectral data can effectively reduce the variation in detected radiance due to changes in forest illumination, progress the classification of forest cover.

• Journal of Korean Ophthalmic Optics Society
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• v.18 no.4
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• pp.549-554
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• 2013

Purpose: To determine the minimal illumination for visual acuity with the decimal vision chart and individual difference with varying contrast and illumination. Methods: Landolt's vision chart with 10 different grade of contrast was made. Minimal illumination was measured for 69 eyes using 100% contrast vision chart. Minimal contrast for identifying the chart was measured in conditions of the minimal illumination and 230 lx, respectively. Results: Minimal illumination was gradually increased with decrease of the chart size. Mean of minimal illumination to identify the 1.0 visual acuity was $74.39{\pm}25.90$ lx with range of 17~107 lx. In conditions of the minimal illumination and 230 lx, the minimal contrast for identifying the chart were gradually increased with decrease of the chart size in both conditions, the those deviation for 69 eyes was also increased. Conclusions: For refractive correction, examiners need to consider the individual difference for identifying the visual chart according to illumination and contrast.

• Korean Journal of Optics and Photonics
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• v.34 no.2
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• pp.61-65
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• 2023

This paper studies a method of applying pre-distortion to the image mask of the gobo illumination optical system to correct an irradiated image and irradiate a clear image. In the case of the gobo illumination optical system, since it is generally irradiated with a tilt, distortion in the upper and lower directions occurs severely in the image. To solve this problem, the correction coordinates of the image were derived using a proportional equation, and the distortion was corrected by applying them to the image mask. As a result, it was confirmed that the distortion was reduced by 64.5% compared to the case of using the existing image mask.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.439-445
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• 2021

Low-cost, ultra-high-speed cameras, made possible by the development of image sensors and small displays, can be very useful in image processing and pattern recognition. This paper introduces an algorithm that corrects irregular lighting from a high-speed image that is continuously input with a slight time interval, and which then obtains an exposed skin color region that is the area of interest in a person from the corrected image. In this study, the non-uniform lighting effect from a received high-speed image is first corrected using a frame blending technique. Then, the region of interest is robustly obtained from the input high-speed color image by applying an elliptical skin color distribution model generated from iterative learning in advance. Experimental results show that the approach presented in this paper corrects illumination in various types of color images, and then accurately acquires the region of interest. The algorithm proposed in this study is expected to be useful in various types of practical applications related to image recognition, such as face recognition and tracking, lighting correction, and video indexing and retrieval.