• The Transactions of The Korean Institute of Electrical Engineers
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• 제61권12호
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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.

• International conference on construction engineering and project management
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.224-229
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• 2009

Digital image recognition has been used for steel bridge surface assessment since late 1990s. However, the non-uniform illumination problems such as shades, shadows, and highlights are still challenges in image processing to date. Therefore, this paper develops a new approach to tackle the non-uniform illumination problem for rust image adjustment. The inhomogeneous illumination problem is divided into shades/shadows and highlights in this paper. The proposed BEMD-morphology approach (BMA) utilizes the bidimensional empirical mode decomposition to mitigate the shade/shadow effect, and the morphological processing to detect and replace the highlight area. Finally, the rust image processed with the BMA will be segmented by the K-Means algorithm, one of the most popular and effective methods, to show the effectiveness of illumination adjustment.

• Journal of Broadcast Engineering
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• 제22권2호
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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.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2011년도 춘계학술발표대회 논문집
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• pp.269-274
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• 2011

A solar cell is primary parts to produce electrical energy from the Sun. And, we can utilize those solar cells as a power generation system in home, factory, and so on. In order to make proper power, the solar cells are configured in series and parallel lay down. In condition of uniform illumination, the solar array will produce an enough power by photovoltaic effects from the solar cells. In case of non-uniform illumination on the solar cells, the power will be dramatically decreased compared to design. Fortunately, there were so many research outputs regarding the illumination effects on solar array. In this work, we tried to find out the non-uniform effects on unit CPV solar cell, because there were no research outputs for unit CPV solar cell considering illumination. The CPV solar cell was used in CPV system to make a power by the Sun. We chosen the triple junction solar cell of GaAsInP2Ge for simulation, which has a 30 % of conversion efficiency. By simulation, we obtained the output performance of CPV solar cells in condition of various illumination by using Hamming Window function. Its performance was degraded by 10 % to 50 % depending illumination conditions.

• International conference on construction engineering and project management
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.449-456
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• 2009

Image processing has been applied to steel bridge defect recognition since 1990s. Compare to human visual inspection, image processing provides a more objective and accurate way of assessment. Since shade and shadow may sometimes occur when taking bridge coating images, non-uniform illumination problems should be considered. By means of color image processing, this paper aims to mitigate the illumination effect for bridge coating assessment. Furthermore, the adaptable ellipse method (AEM) is proposed to recognize mild rust colors. Finally, AEM will be compared to the K-Means algorithm, a popular recognition method, to show its advantage.

• International conference on construction engineering and project management
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.257-262
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• 2009

Image processing has been utilized for assessment of infrastructure surface coating conditions for years. However, there is no robust method to overcome the non-uniform illumination problem to date. Therefore, this paper aims to deal with non-uniform illumination problems for bridge coating assessment and to achieve automated rust intensity recognition. This paper starts with selection of the best color configuration for non-uniformly illuminated rust image segmentation. The adaptive-network-based fuzzy inference system (ANFIS) is adopted as the framework to develop the new model, the box-and-ellipse-based neuro-fuzzy approach (BENFA). Finally, the performance of BENFA is compared to the Fuzzy C-Means (FCM) method, which is often used in image recognition, to show the advantage and robustness of BENFA.

• Journal of KIISE
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• 제44권3호
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• pp.295-305
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• 2017

Facial appearance is greatly influenced by illumination conditions, and therefore illumination variation is one of the factors that degrades performance of face recognition systems. In this paper, we propose a robust method for face representation under varying illumination conditions, combining non-alpha Weberface (non-alpha WF) and histogram equalization. We propose a two-step method: (1) for a given face image, non-alpha WF, which is not applied a parameter for adjusting the intensity difference between neighboring pixels in WF, is computed; (2) histogram equalization is performed to non-alpha WF, to make a uniform histogram distribution globally and to enhance the contrast. $(2D)^2PCA$ is applied to extract low-dimensional discriminating features from the preprocessed face image. Experimental results on the extended Yale B face database and the CMU PIE face database show that the proposed method yielded better recognition rates than several illumination processing methods as well as the conventional WF, achieving average recognition rates of 93.31% and 97.25%, respectively.

• Journal of Korea Multimedia Society
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• 제11권12호
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• pp.1649-1657
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• 2008

In this paper, to overcome the failure of binarization for the characters suffered from low contrast and non-uniform illumination in license plate character recognition system, we improved the binarization method by combining local thresholding with global thresholding and edge detection. Firstly, apply the local thresholding method to locate the characters in the license plate image and then get the threshold value for the character based on edge detector. This method solves the problem of local low contrast and non-uniform illumination. Finally, back-propagation Neural Network is selected as a powerful tool to perform the recognition process. The results of the experiments i1lustrate that the proposed binarization method works well and the selected classifier saves the processing time. Besides, the character recognition system performed better recognition accuracy 95.7%, and the recognition speed is controlled within 0.3 seconds.

• Journal of IKEEE
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• 제22권4호
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• pp.1188-1194
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• 2018

This paper proposes an image enhancement-based license plate detection algorithm to improve the overall performance of system. Non-uniform illumination conditions have huge impact on overall plate detection system accuracy. In this paper, we propose an algorithm for color image enhancement-based license plate detection for improving accuracy of images degraded by excessively strong and low sunlight. Firstly, the image is enhanced by Multi-Scale Retinex algorithm. Secondly, a plate detection method is employed to take advantage of geometric properties of connected components, which can significantly reduce the undesired plate regions. Finally, intersection over union method is applied for detecting the accurate location of number plate. Experimental results show that the proposed method significantly improves the accuracy of plate detection system.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제17권2호
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• pp.423-430
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• 2013

Recently, the personal identification technologies using vein pattern of back of the hand, palm, and finger have been developed actively because it has the advantage that the vein blood vessel in the body is impossible to damage, make a replication and forge. However, it is difficult to extract clearly the vein region from captured vein images through common image prcessing based region segmentation method, because of the light scattering and non-uniform internal tissue by skin layer and inside layer skeleton, etc. Especially, it takes a long time for processing time and makes a discontinuity of blood vessel just in a image because it has non-uniform illumination due to use a locally different adaptive threshold for the binarization of acquired finger-vein image. To solve this problem, we propose illumination normalization based fast method for extracting the finger-vein region. The proposed method has advantages compared to the previous methods as follows. Firstly, for remove a non-uniform illumination of the captured vein image, we obtain a illumination component of the captured vein image by using a low-pass filter. Secondly, by extracting the finger-vein path using one time binarization of a single threshold selection, we were able to reduce the processing time. Through experimental results, we confirmed that the accuracy of extracting the finger-vein region was increased and the processing time was shortened than prior methods.